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GeezerVison is showing orlitany.github.io — Or Litany - 3D Computer Vision & Generative AI Researcher

Or Litany

or dot litany at gmail dot com

I'm a Senior Research Scientist at NVIDIA Research and an Assistant Professor at the Technion, specializing in 3D computer vision and generative AI. I'm honored to be a 2023 Azrieli Faculty Fellow and a Taub Fellow. Previously, I conducted postdoctoral research at Stanford University under Prof. Leonidas Guibas, and at FAIR, hosted by Prof. Jitendra Malik. My PhD is from Tel-Aviv University, advised by Prof. Alex Bronstein. My B.Sc. in Physics and Mathematics is from the Hebrew University.

CV / / / /

Or Litany at Yosemite National Park

News

  • [Sep 25, 2026] Two papers accepted to NeurIPS 2026!
  • [Aug 17, 2026] Retrieval-Augmented Gaussian Avatars accepted to the Interactive Social Avatars (ISA) workshop at ECCV 2026!
  • [Nov, 2025] "Appreciate the View" is accepted at 3DV 2026.
  • [August, 2025] "Gaussian See, Gaussian Do" accepted at SIGGRAPH-ASIA 2025.
  • [June, 2025] Two papers accepted at ICCV 2025.
  • [May, 2025] "FRIDU" is accepted at SGP 2025.
  • [March, 2025] Honored to chair the Research Interaction sessions at the upcoming 3DV 2026.
  • [Feb 12, 2025] OmniRe got a spotlight at ICLR 2025.
  • [Feb 2, 2025] I will serve as an Area Chair for the upcoming ICCV 2025.
  • [Jan 5, 2025] Epi-NAF is accepted at ISBI 2025 as an Oral.
  • [Dec 21, 2024] Two workshops accepted at CVPR 2025.
  • [June 18, 2026] Two papers accepted to ECCV 2026!
  • [May 19, 2026] Honored to receive the Outstanding Area Chair award at CVPR 2026.
  • [May 1, 2026] Test-Time Training with KV Binding accepted to ICML 2026!
  • [Mar 28, 2026] Prox-E accepted to SIGGRAPH 2026!
  • [Feb 21, 2026] Three papers accepted to CVPR 2026!
  • [Jan 26, 2026] Two papers accepted to ICLR 2026!
  • [Dec 22, 2025] Our workshop "OpenSUN3D: Open-World 3D Scene Understanding with Foundation Models", has been accepted as a Half-Day workshop at CVPR 2026!
  • [Dec, 2025] Grateful to Meta for awarding an Academic Gift to support our lab's research.

Students

I am actively seeking talented and motivated Postdoctoral and PhD candidates to join my new lab at the Technion. To get a sense of the research areas I am most passionate about, I encourage you to explore my recent publications and invited talks. As an ELLIS scholar, I also invite eligible candidates to consider applying through the ELLIS PhD and Postdoc Program.

13 current • 15 alumni • 5 PhD • 6 MSc • 1 Postdoc • 1 Intern▶

PhD (5)

  • Tomer Borreda (2026-present)
  • Ido Sobol (2025-present)
  • Daniel Gilo (2024-present)
  • Gal Harari (2024-present)
  • Assaf Singer (2024-present)

MSc (6)

  • Ido Raizman (2026-present)
  • Maroun Khriesh (2026-present)
  • Nitzan Leshem (2025-present)
  • Merav Keidar (2025-present)
  • Roi Teichman (2025-present) — Joint advising with Prof. Oren Salzman
  • Amir Mann (2025-present)

Postdoc (1)

  • Matan Levy (2026-present) — Joint advising with Prof. Hadar Elor

Intern (1)

  • Noam Rotstein (2026-present)

MSc (4)

  • Tomer Borreda (2026)
  • Yarin Bekor (2025)
  • Saar Stern (2025)
  • Guy Levavi (2024) — Joint advising with Prof. Assaf Marom

Postdoc (1)

  • Fangqiang Ding (2025) — Postdoc at MIT

Intern (10)

  • Junchen Liu (2026)
  • Chenfeng Xu (2023) — Assistant professor at UT Austin
  • Davis Rempe (2023) — Research Scientist at Nvidia
  • Shengyu Huang (2023) — Research Scientist at Nvidia
  • Tzofi Klinghoffer (2023) — PhD at MIT Media Lab
  • Zan Gojcic (2022) — Sr. Research Manager at Nvidia
  • Francis Williams (2022) — Sr. Research Scientist at Nvidia
  • Derek Liu (2022) — Sr. Research Scientist at Roblox and an Adjunct Professor at UBC
  • Ge Zhang (2021) — Software Engineer at Righthand Robotics — Summer intern at Stanford University
  • Cinjon Resnick (2021) — Research Scientist at Sesame

Teaching

  • Deep Learning (CS 02360781)

    An introductory course covering the fundamentals of deep learning, neural networks, and their applications in computer vision and natural language processing.

  • Compter Vision (CS 02360873) - Course Page

    Topics in computer vision including classic methods like hough voting and RANSAC, multiview stereo, and modren methods like vision transformers and generative modeling.

  • 3D Computer Vision Seminar (CS 02360007) - Course Page

    Advanced topics in 3D computer vision including point cloud processing, neural rendering, and 3D scene understanding.

Invited talks

  • Seeing by Generating: NVS as a route to 3D understanding. Slides
  • How to train and steer generative models in 3D, motion, 2D and video.
  • VoteNet and ImVoteNet. Slides Video
  • Geometric Deep Learning: Introduction. Slides Video
  • Deep Learning for “Exotic” Data Like 3D Meshes and Point-Clouds. Slides Video
  • Deep Hough Voting for 3D object detection in point clouds. Slides Video
  • SOSELETO: A Unified Approach to Transfer Learning and Training with Noisy Labels. Slides Video
  • Lights, Camera, Action! Revolutionizing Computer Vision with Video Generative AI. Video
  • EmerNeRF: Emergent Spatial-Temporal Scene Decomposition via Self-Supervision. Video
  • Data-driven simulation for AV. Slides Video
  • Data-driven simulation for AV (short). Slides
  • Manipulating neural fields. Slides Video
  • 3D scene understanding from pointclouds. Video
  • PointContrast. Slides
  • Latent Canonicalizers. Slides Video

Workshops / Tutorials

  • Open-Vocabulary 3D Scene Understanding 6th workshop at CVPR, 2026.
  • Open-Vocabulary 3D Scene Understanding 5th workshop at ICCV, 2025.
  • 3DOVScene: Open-Vocabulary 3D Scene Understanding workshop at ICCV, 2023.
  • Neural Fields in Computer Vision workshop at CVPR, 2022.
  • Learning 3D Representations for Shape and Appearance workshop at ICCV, 2021.
  • iGDL: Israeli Geometric Deep Learning workshop (First) workshop, 2020.
  • iGDL: Israeli Geometric Deep Learning workshop (Second) workshop, 2021.
  • Learning 3D Representations for Shape and Appearance workshop at ECCV, 2020.
  • Deep Learning for Computer Graphics and Geometry Processing tutorial at Eurographics, 2019.
  • Deep Learning meets Geometry tutorial at ECCV, 2018.
  • Deep Learning and Geometry workshop at EUSIPCO, 2017.
  • Open-Vocabulary 3D Scene Understanding 4th workshop at CVPR, 2025.
  • Neural Fields Beyond Conventional Cameras 2nd workshop at CVPR, 2025.
  • Neural Fields Beyond Conventional Cameras workshop at ECCV, 2024.
  • Open-Vocabulary 3D Scene Understanding 3rd workshop at ECCV, 2024.
  • Open-Vocabulary 3D Scene Understanding 2nd workshop at CVPR, 2024.
  • Data-Driven Autonomous Driving Simulation workshop at CVPR, 2024.
  • Neural Fields for Visual Computing workshop at CVPR, 2024.
  • Neural Fields for Visual Computing Course at SIGGRAPH, 2023.

Press

  • June 2026: Technion tool lets users create AI videos by mouse
  • Nov 2023: NVIDIA technical blog: Using Synthetic Data to Address Novel Viewpoints for Autonomous Vehicle Perception
  • July 2023: NVIDIA technical blog: Sensing New Frontiers with Neural Lidar Fields for Autonomous Vehicle Simulation
  • September 2022: Interview for UnboxingAI podcast
  • March 2022: NVIDIA Showcases Novel AI Tools in DRIVE Sim to Advance Autonomous Vehicle Development
  • July 2020: Stanford makes an impact at machine learning conference
  • July 2020: חוקרי אנבידיה זכו בפרס עבודת המחקר המצטיינת בכנס הבינלאומי המוביל בעולם ללמידת מכונה (ICML)

Publications

2026

ReLift: Dense 3D Tracking as Lifted Trajectory Repair

Assaf Singer, Maroun Khriesh, Noam Rotstein, Yoni Kasten, Or Litany

Preprint

paper / code / page / tweet /
@misc{singer2026reliftdense3dtracking,
  title = {ReLift: Dense 3D Tracking as Lifted Trajectory Repair},
  author = {Assaf Singer and Maroun Khriesh and Noam Rotstein and Yoni Kasten and Or Litany},
  year = {2026},
  venue = {Preprint},
  eprint = {2610.42136},
  archiveprefix = {arXiv},
  primaryclass = {cs.CV},
  url = {https://arxiv.org/abs/2610.42136},
  image = {./OL_files/relift_teaser.mp4},
  paper = {https://arxiv.org/abs/2610.42136},
  code = {https://github.com/ReLift3D/ReLift},
  page = {https://relift3d.github.io/},
  tweet = {https://x.com/assaf_singer/status/2117141154026201529?a=e3G98sEAP-UfbJYPh2Y&s=20}
}
VideoMDM: Towards 3D Human Motion Generation From 2D Supervision

VideoMDM: Towards 3D Human Motion Generation From 2D Supervision

Amir Mann, Gal Michael Harari, Merav Keidar, Or Litany

NeurIPS 2026

paper / page / tweet /
@misc{mann2026videomdm3dhumanmotion,
  title = {VideoMDM: Towards 3D Human Motion Generation From 2D Supervision},
  author = {Amir Mann and Gal Michael Harari and Merav Keidar and Or Litany},
  year = {2026},
  venue = {NeurIPS 2026},
  eprint = {2606.13364},
  archiveprefix = {arXiv},
  primaryclass = {cs.LG},
  url = {https://arxiv.org/abs/2606.13364},
  image = {./OL_files/videomdm_method.png},
  paper = {https://arxiv.org/abs/2606.13364},
  page = {https://videomdm.github.io/},
  tweet = {https://x.com/orlitany/status/2065344454798500325?s=20}
}
Learnable Spectral Activations

Learnable Spectral Activations

Tamir Shor, Or Litany, Alex Bronstein

NeurIPS 2026

paper / code / tweet /
@misc{shor2026learnablespectralactivations,
  title = {Learnable Spectral Activations},
  author = {Tamir Shor and Or Litany and Alex Bronstein},
  year = {2026},
  venue = {NeurIPS 2026},
  eprint = {2610.07419},
  archiveprefix = {arXiv},
  primaryclass = {cs.LG},
  url = {https://arxiv.org/abs/2610.07419},
  image = {./OL_files/lsa_teaser.webp},
  paper = {https://arxiv.org/abs/2610.07419},
  code = {https://github.com/tamirshor7/Learnable-Spectral-Activations},
  tweet = {https://x.com/orlitany/status/2113334247343751647?s=20}
}
Joints, Camera, Action! Co-Generating 3D Motion and Video for Arbitrary Rigs

Joints, Camera, Action! Co-Generating 3D Motion and Video for Arbitrary Rigs

Noam Rotstein, Yoad Tewel, Chen Tessler, Haggai Maron, Gal Chechik, Or Litany, Yoni Kasten, Yuval Atzmon

Preprint

paper / page / tweet /
@misc{rotstein2026jointscameraactioncogenerating,
  title = {Joints, Camera, Action! Co-Generating 3D Motion and Video for Arbitrary Rigs},
  author = {Noam Rotstein and Yoad Tewel and Chen Tessler and Haggai Maron and Gal Chechik and Or Litany and Yoni Kasten and Yuval Atzmon},
  year = {2026},
  venue = {Preprint},
  eprint = {2610.28632},
  archiveprefix = {arXiv},
  primaryclass = {cs.CV},
  url = {https://arxiv.org/abs/2610.28632},
  image = {./OL_files/jca_teaser.webp},
  paper = {https://arxiv.org/abs/2610.28632},
  page = {https://research.nvidia.com/labs/par/projects/jca/},
  tweet = {https://x.com/NoamRot/status/2112926067979702621?s=20}
}
DyRAD: Radar Novel View Synthesis for Dynamic Driving Scenes

DyRAD: Radar Novel View Synthesis for Dynamic Driving Scenes

Merav Keidar, Tomer Borreda, Rajalakshmi Nandakumar, Or Litany

Preprint

paper / code / page / tweet /
@misc{keidar2026dyradradarnovelview,
  title = {DyRAD: Radar Novel View Synthesis for Dynamic Driving Scenes},
  author = {Merav Keidar and Tomer Borreda and Rajalakshmi Nandakumar and Or Litany},
  year = {2026},
  venue = {Preprint},
  eprint = {2609.39841},
  archiveprefix = {arXiv},
  primaryclass = {cs.CV},
  url = {https://arxiv.org/abs/2609.39841},
  image = {./OL_files/dyrad_teaser.webp},
  paper = {https://arxiv.org/abs/2609.39841},
  code = {https://github.com/Dyrad-NVS/DyRAD},
  page = {https://dyrad-nvs.github.io/},
  tweet = {https://x.com/orlitany/status/2106019515037610379?s=20}
}

WarpHammer: Densifying Scene Warps with 3D Object Priors for Extreme View Synthesis

Michael Green, Gavriel Habib, Dvir Samuel, Tal Berkovitz Shalev, Issar Tzachor, Rami Ben-Ari, Or Litany

Preprint

paper / page /
@misc{green2026warphammerdensifyingscenewarps,
  title = {WarpHammer: Densifying Scene Warps with 3D Object Priors for Extreme View Synthesis},
  author = {Michael Green and Gavriel Habib and Dvir Samuel and Tal {Berkovitz Shalev} and Issar Tzachor and Rami Ben-Ari and Or Litany},
  year = {2026},
  venue = {Preprint},
  eprint = {2606.31258},
  archiveprefix = {arXiv},
  primaryclass = {cs.CV},
  url = {https://arxiv.org/abs/2606.31258},
  image = {./OL_files/warphammer_teaser.mp4},
  paper = {https://arxiv.org/abs/2606.31258},
  page = {https://pihash2k.github.io/extreme_nvs/}
}
FlowBender: Feedback-Aware Training for Self-Correcting Conditional Flows

FlowBender: Feedback-Aware Training for Self-Correcting Conditional Flows

Daniel Gilo, Sven Elflein, Ido Sobol, Or Litany

Preprint

paper / page / tweet /
@misc{gilo2026flowbenderfeedbackawaretrainingselfcorrecting,
  title = {FlowBender: Feedback-Aware Training for Self-Correcting Conditional Flows},
  author = {Daniel Gilo and Sven Elflein and Ido Sobol and Or Litany},
  year = {2026},
  venue = {Preprint},
  eprint = {2606.20404},
  archiveprefix = {arXiv},
  primaryclass = {cs.CV},
  url = {https://arxiv.org/abs/2606.20404},
  image = {./OL_files/teaser_flowbender.jpg},
  paper = {https://arxiv.org/abs/2606.20404},
  page = {https://flow-bender.github.io/},
  tweet = {https://x.com/danielgilo1/status/2067986128766951885?s=20}
}
SceneTeract: Agentic Functional Affordances and VLM Grounding in 3D Scenes

SceneTeract: Agentic Functional Affordances and VLM Grounding in 3D Scenes

Léopold Maillard, Francis Engelmann, Tom Durand, Boxiao Pan, Yang You, Or Litany, Leonidas Guibas, Maks Ovsjanikov

Preprint

paper / page /
@misc{maillard2026sceneteract,
  title = {{SceneTeract: Agentic Functional Affordances and VLM Grounding in 3D Scenes}},
  author = {Maillard, L{\'e}opold and Engelmann, Francis and Durand, Tom and Pan, Boxiao and You, Yang and Litany, Or and Guibas, Leonidas and Ovsjanikov, Maks},
  year = {2026},
  venue = {Preprint},
  eprint = {2603.29798},
  archiveprefix = {arXiv},
  primaryclass = {cs.CV},
  url = {https://arxiv.org/abs/2603.29798},
  image = {./OL_files/teaser_sceneteract.jpg},
  paper = {https://arxiv.org/abs/2603.29798},
  page = {https://sceneteract.github.io/}
}

SpectralSplats: Robust Differentiable Tracking via Spectral Moment Supervision

Avigail Cohen Rimon, Amir Mann, Mirela Ben-Chen, Or Litany

ECCV 2026

paper / page / tweet /
@misc{rimon2026spectralsplatsrobustdifferentiabletracking,
  title = {SpectralSplats: Robust Differentiable Tracking via Spectral Moment Supervision},
  author = {Avigail {Cohen Rimon} and Amir Mann and Mirela Ben-Chen and Or Litany},
  year = {2026},
  venue = {ECCV 2026},
  eprint = {2603.24036},
  archiveprefix = {arXiv},
  primaryclass = {cs.CV},
  url = {https://arxiv.org/abs/2603.24036},
  image = {./OL_files/spectralsplats_teaser.mp4},
  paper = {https://arxiv.org/abs/2603.24036},
  page = {https://avigailco.github.io/SpectralSplats/},
  tweet = {https://x.com/orlitany/status/2037133567910674747}
}
RadarGen: Automotive Radar Point Cloud Generation from Cameras

RadarGen: Automotive Radar Point Cloud Generation from Cameras

Tomer Borreda, Fangqiang Ding, Sanja Fidler, Shengyu Huang, Or Litany

ECCV 2026

paper / page / tweet /
@misc{borreda2025radargenautomotiveradarpoint,
  title = {RadarGen: Automotive Radar Point Cloud Generation from Cameras},
  author = {Tomer Borreda and Fangqiang Ding and Sanja Fidler and Shengyu Huang and Or Litany},
  year = {2025},
  venue = {ECCV 2026},
  eprint = {2512.17897},
  archiveprefix = {arXiv},
  primaryclass = {cs.CV},
  url = {https://arxiv.org/abs/2512.17897},
  image = {./OL_files/radargen_teaser.jpg},
  paper = {https://arxiv.org/abs/2512.17897},
  page = {https://radargen.github.io/},
  video = {https://www.youtube.com/watch?v=-g4zf8DzJDo},
  tweet = {https://x.com/TomerBorreda/status/2002974157911593179}
}
Retrieval-Augmented Gaussian Avatars: Improving Expression Generalization

Retrieval-Augmented Gaussian Avatars: Improving Expression Generalization

Matan Levy, Gavriel Habib, Issar Tzachor, Dvir Samuel, Rami Ben-Ari, Nir Darshan, Or Litany, Dani Lischinski

ECCV 2026 Workshop on Interactive Social Avatars (ISA)

paper /
@misc{levy2026retrievalaugmentedgaussianavatarsimproving,
  title = {Retrieval-Augmented Gaussian Avatars: Improving Expression Generalization},
  author = {Matan Levy and Gavriel Habib and Issar Tzachor and Dvir Samuel and Rami Ben-Ari and Nir Darshan and Or Litany and Dani Lischinski},
  year = {2026},
  venue = {ECCV 2026 Workshop on Interactive Social Avatars (ISA)},
  eprint = {2603.08645},
  archiveprefix = {arXiv},
  primaryclass = {cs.CV},
  url = {https://arxiv.org/abs/2603.08645},
  image = {./OL_files/teaser_RAGaussianAvaters.jpg},
  paper = {https://arxiv.org/abs/2603.08645}
}
Prox-E: Fine-Grained 3D Shape Editing via Primitive-Based Abstractions

Prox-E: Fine-Grained 3D Shape Editing via Primitive-Based Abstractions

Etai Sella, Hao Phung, Nitay Amiel, Or Litany, Or Patashnik, Hadar Averbuch-Elor

SIGGRAPH 2026

paper / page / tweet /
@misc{sella2026proxefinegrained3dshape,
  title = {Prox-E: Fine-Grained 3D Shape Editing via Primitive-Based Abstractions},
  author = {Etai Sella and Hao Phung and Nitay Amiel and Or Litany and Or Patashnik and Hadar Averbuch-Elor},
  year = {2026},
  venue = {SIGGRAPH 2026},
  eprint = {2604.23774},
  archiveprefix = {arXiv},
  primaryclass = {cs.GR},
  url = {https://arxiv.org/abs/2604.23774},
  image = {./OL_files/teaser_proxe.png},
  paper = {https://arxiv.org/abs/2604.23774},
  page = {https://etaisella.github.io/Prox-E/},
  tweet = {https://x.com/etai_sella/status/2051284611552936127?s=20}
}
Test-Time Training with KV Binding Is Secretly Linear Attention

Test-Time Training with KV Binding Is Secretly Linear Attention

Junchen Liu, Sven Elflein, Or Litany, Zan Gojcic, Ruilong Li

ICML 2026

paper / page / tweet /
@misc{liu2026testtimetrainingkvbinding,
  title = {Test-Time Training with KV Binding Is Secretly Linear Attention},
  author = {Junchen Liu and Sven Elflein and Or Litany and Zan Gojcic and Ruilong Li},
  year = {2026},
  venue = {ICML 2026},
  eprint = {2602.21204},
  archiveprefix = {arXiv},
  primaryclass = {cs.LG},
  url = {https://arxiv.org/abs/2602.21204},
  image = {./OL_files/tttlinear_teaser.jpg},
  paper = {https://arxiv.org/abs/2602.21204},
  page = {https://research.nvidia.com/labs/sil/projects/tttla/},
  tweet = {https://x.com/JunchenLiu77/status/2026665572755198224}
}
Realiz3D: 3D Generation Made Photorealistic via Domain-Aware Learning

Realiz3D: 3D Generation Made Photorealistic via Domain-Aware Learning

Ido Sobol, Kihyuk Sohn, Yoav Blum, Egor Zakharov, Max Bluvstein, Andrea Vedaldi, Or Litany

CVPR 2026

paper / page / tweet /
@inproceedings{sobol2026realiz3d,
  title = {{Realiz3D}: {3D} Generation Made Photorealistic via Domain-Aware Learning},
  author = {Ido Sobol and Kihyuk Sohn and Yoav Blum and Egor Zakharov and Max Bluvstein and Andrea Vedaldi and Or Litany},
  year = {2026},
  venue = {CVPR 2026},
  booktitle = {Proceedings of the {IEEE}/CVF Conference on Computer Vision and Pattern Recognition ({CVPR})},
  image = {./OL_files/realiz3d_teaser.jpg},
  paper = {https://idosobol.github.io/realiz3d/realiz3d_paper.pdf},
  page = {https://idosobol.github.io/realiz3d/},
  tweet = {https://x.com/IdoSobol/status/2040039788103754206?s=20}
}
InstructMix2Mix: Consistent Sparse-View Editing Through Multi-View Model Personalization

InstructMix2Mix: Consistent Sparse-View Editing Through Multi-View Model Personalization

Daniel Gilo, Or Litany

CVPR 2026

paper / code / page / tweet /
@misc{gilo2025instructmix2mixconsistentsparseviewediting,
  title = {InstructMix2Mix: Consistent Sparse-View Editing Through Multi-View Model Personalization},
  author = {Daniel Gilo and Or Litany},
  year = {2025},
  venue = {CVPR 2026},
  eprint = {2511.14899},
  archiveprefix = {arXiv},
  primaryclass = {cs.CV},
  url = {https://arxiv.org/abs/2511.14899},
  image = {./OL_files/teaser_IM2M.png},
  paper = {https://www.arxiv.org/abs/2511.14899},
  page = {https://danielgilo.github.io/instruct-mix2mix/},
  code = {https://github.com/DanielGilo/instruct-mix2mix/tree/main},
  tweet = {https://x.com/orlitany/status/2026628621968789738?s=20}
}
DiffusionHarmonizer: Bridging Neural Reconstruction and Photorealistic Simulation with Online Diffusion Enhancer

DiffusionHarmonizer: Bridging Neural Reconstruction and Photorealistic Simulation with Online Diffusion Enhancer

Yuxuan Zhang, Katarı́na Tóthová, Zian Wang, Kangxue Yin, Haithem Turki, Riccardo de Lutio, Yen-Yu Chang, Or Litany, Sanja Fidler, Zan Gojcic

CVPR 2026

paper / page /
@article{zhang2026diffusionharmonizer,
  title = {DiffusionHarmonizer: Bridging Neural Reconstruction and Photorealistic Simulation with Online Diffusion Enhancer},
  author = {Zhang, Yuxuan and T{\'o}thov{\'a}, Katar{\'\i}na and Wang, Zian and Yin, Kangxue and Turki, Haithem and de Lutio, Riccardo and Chang, Yen-Yu and Litany, Or and Fidler, Sanja and Gojcic, Zan},
  year = {2026},
  venue = {CVPR 2026},
  journal = {arXiv preprint arXiv:2602.24096},
  image = {./OL_files/harmonizer_teaser.gif},
  paper = {https://arxiv.org/abs/2602.24096},
  page = {https://research.nvidia.com/labs/sil/projects/diffusion-harmonizer/}
}
Time-to-Move: Training-Free Motion Controlled Video Generation via Dual-Clock Denoising

Time-to-Move: Training-Free Motion Controlled Video Generation via Dual-Clock Denoising

Assaf Singer, Noam Rotstein, Amir Mann, Ron Kimmel, Or Litany

ICLR 2026

paper / code / page / tweet /
@misc{singer2025timetomovetrainingfreemotioncontrolled,
  title = {Time-to-Move: Training-Free Motion Controlled Video Generation via Dual-Clock Denoising},
  author = {Assaf Singer and Noam Rotstein and Amir Mann and Ron Kimmel and Or Litany},
  year = {2025},
  venue = {ICLR 2026},
  eprint = {2511.08633},
  archiveprefix = {arXiv},
  primaryclass = {cs.CV},
  url = {https://arxiv.org/abs/2511.08633},
  image = {./OL_files/teaser_T2M.png},
  paper = {https://arxiv.org/abs/2511.08633},
  page = {https://time-to-move.github.io/},
  code = {https://github.com/time-to-move/TTM},
  tweet = {https://x.com/assaf_singer/status/1988967522033647618}
}
SpaceControl: Introducing Test-Time Spatial Control to 3D Generative Modeling

SpaceControl: Introducing Test-Time Spatial Control to 3D Generative Modeling

Elisabetta Fedele, Francis Engelmann, Ian Huang, Or Litany, Marc Pollefeys, Leonidas Guibas

ICLR 2026

paper / code / page / tweet /
@misc{fedele2025spacecontrolintroducingtesttimespatial,
  title = {SpaceControl: Introducing Test-Time Spatial Control to 3D Generative Modeling},
  author = {Elisabetta Fedele and Francis Engelmann and Ian Huang and Or Litany and Marc Pollefeys and Leonidas Guibas},
  year = {2025},
  venue = {ICLR 2026},
  eprint = {2512.05343},
  archiveprefix = {arXiv},
  primaryclass = {cs.CV},
  url = {https://arxiv.org/abs/2512.05343},
  image = {./OL_files/teaser_supergen.png},
  paper = {https://arxiv.org/abs/2512.05343},
  page = {https://spacecontrol3d.github.io/},
  code = {https://github.com/spacecontrol3d/spacecontrol},
  tweet = {https://x.com/efedele16/status/1997978439719305725}
}
Appreciate the View: A Task-Aware Evaluation Framework for Novel View Synthesis

Appreciate the View: A Task-Aware Evaluation Framework for Novel View Synthesis

Saar Stern, Ido Sobol, Or Litany

3DV 2026

paper / code / page / tweet /
@misc{stern2025appreciateviewtaskawareevaluation,
  title = {Appreciate the View: A Task-Aware Evaluation Framework for Novel View Synthesis},
  author = {Saar Stern and Ido Sobol and Or Litany},
  year = {2025},
  venue = {3DV 2026},
  eprint = {2511.12675},
  archiveprefix = {arXiv},
  primaryclass = {cs.CV},
  url = {https://arxiv.org/abs/2511.12675},
  image = {./OL_files/teaser_AppreciatetheView.png},
  paper = {https://arxiv.org/abs/2511.12675},
  page = {https://saarst.github.io/appreciate-the-view-website/},
  code = {https://github.com/saarst/appreciate-the-view},
  tweet = {https://x.com/SternSaar/status/1991622794925469952}
}

2025

Gaussian See, Gaussian Do: Semantic 3D Motion Transfer from Multiview Video

Gaussian See, Gaussian Do: Semantic 3D Motion Transfer from Multiview Video

Yarin Bekor, Gal Michael Harari, Or Perel, Or Litany

SIGGRAPH-ASIA 2025

paper / page /
@misc{bekor2025gaussianseegaussiando,
  title = {Gaussian See, Gaussian Do: Semantic 3D Motion Transfer from Multiview Video},
  author = {Yarin Bekor and Gal Michael Harari and Or Perel and Or Litany},
  year = {2025},
  venue = {SIGGRAPH-ASIA 2025},
  eprint = {2511.14848},
  archiveprefix = {arXiv},
  primaryclass = {cs.CV},
  url = {https://arxiv.org/abs/2511.14848},
  image = {./OL_files/GSGD_teaser.jpg},
  paper = {https://arxiv.org/pdf/2511.14848},
  page = {https://gsgd-motiontransfer.github.io/}
}
A Lesson in Splats: Teacher-Guided Diffusion for 3D Gaussian Splats Generation with 2D Supervision

A Lesson in Splats: Teacher-Guided Diffusion for 3D Gaussian Splats Generation with 2D Supervision

Chensheng Peng, Ido Sobol, Masayoshi Tomizuka, Kurt Keutzer, Chenfeng Xu, Or Litany

ICCV 2025

paper / page /
@article{peng2024lessonsplatsteacherguideddiffusion,
  title = {A Lesson in Splats: Teacher-Guided Diffusion for 3D Gaussian Splats Generation with 2D Supervision},
  author = {Chensheng Peng and Ido Sobol and Masayoshi Tomizuka and Kurt Keutzer and Chenfeng Xu and Or Litany},
  year = {2025},
  venue = {ICCV 2025},
  journal = {ICCV},
  url = {https://arxiv.org/abs/2412.00623},
  image = {./OL_files/lessonInSplats.png},
  paper = {https://arxiv.org/abs/2412.00623},
  page = {https://lesson-in-splats.github.io/}
}
MonSTeR: a Unified Model for Motion, Scene, Text Retrieval

MonSTeR: a Unified Model for Motion, Scene, Text Retrieval

Luca Collorone, Matteo Gioia, Massimiliano Pappa, Paolo Leoni, Giovanni Ficarra, Or Litany, Indro Spinelli, Fabio Galasso

ICCV 2025

paper / code / tweet /
@article{collorone2025monster,
  title = {MonSTeR: a Unified Model for Motion, Scene, Text Retrieval},
  author = {Collorone, Luca and Gioia, Matteo and Pappa, Massimiliano and Leoni, Paolo and Ficarra, Giovanni and Litany, Or and Spinelli, Indro and Galasso, Fabio},
  year = {2025},
  venue = {ICCV 2025},
  journal = {ICCV},
  image = {./OL_files/monster_teaser.jpg},
  paper = {https://arxiv.org/abs/2510.03200},
  code = {https://github.com/colloroneluca/MonSTeR?tab=readme-ov-file},
  tweet = {https://x.com/IndroSpinelli/status/1940445067959038357}
}
FRIDU: Functional Map Refinement with Guided Image Diffusion

FRIDU: Functional Map Refinement with Guided Image Diffusion

Avigail Cohen Rimon, Mirela Ben-Chen, Or Litany

SGP 2025

paper / code /
@article{rimon2025fridu,
  title = {FRIDU: Functional Map Refinement with Guided Image Diffusion},
  author = {{Cohen Rimon}, Avigail and Ben-Chen, Mirela and Litany, Or},
  year = {2025},
  venue = {SGP 2025},
  journal = {SGP},
  image = {./OL_files/FRIDU_teaser.jpg},
  paper = {https://arxiv.org/abs/2506.14322},
  code = {https://github.com/avigailco/FRIDU}
}
OmniRe: Omni Urban Scene Reconstruction

OmniRe: Omni Urban Scene Reconstruction

Ziyu Chen, Jiawei Yang, Jiahui Huang, Riccardo de Lutio, Janick Martinez Esturo, Boris Ivanovic, Or Litany, Zan Gojcic, Sanja Fidler, Marco Pavone, Li Song, Yue Wang

ICLR 2025Spotlight

paper / page /
@article{chen2024omnire,
  title = {OmniRe: Omni Urban Scene Reconstruction},
  author = {Ziyu Chen and Jiawei Yang and Jiahui Huang and Riccardo de Lutio and Janick {Martinez Esturo} and Boris Ivanovic and Or Litany and Zan Gojcic and Sanja Fidler and Marco Pavone and Li Song and Yue Wang},
  year = {2024},
  venue = {ICLR 2025},
  journal = {arXiv preprint arXiv:2408.16760},
  image = {./OL_files/omnire.png},
  paper = {https://arxiv.org/abs/2408.16760},
  page = {https://ziyc.github.io/omnire/},
  award = {Spotlight}
}
GAS-NeRF: Geometry-Aware Stylization of Dynamic Radiance Fields

GAS-NeRF: Geometry-Aware Stylization of Dynamic Radiance Fields

Nhat Phuong Anh Vu, Abhishek Saroha, Or Litany, Daniel Cremers

Preprint

paper /
@misc{vu2025gasnerfgeometryawarestylizationdynamic,
  title = {GAS-NeRF: Geometry-Aware Stylization of Dynamic Radiance Fields},
  author = {Nhat Phuong Anh Vu and Abhishek Saroha and Or Litany and Daniel Cremers},
  year = {2025},
  venue = {Preprint},
  eprint = {2503.08483},
  archiveprefix = {arXiv},
  primaryclass = {cs.CV},
  url = {https://arxiv.org/abs/2503.08483},
  image = {./OL_files/GASnerf_teaser.png},
  paper = {https://arxiv.org/abs/2503.08483}
}
ZDySS – Zero-Shot Dynamic Scene Stylization using Gaussian Splatting

ZDySS – Zero-Shot Dynamic Scene Stylization using Gaussian Splatting

Abhishek Saroha, Florian Hofherr, Mariia Gladkova, Cecilia Curreli, Or Litany, Daniel Cremers

Preprint

paper /
@misc{saroha2025zdysszeroshotdynamic,
  title = {ZDySS -- Zero-Shot Dynamic Scene Stylization using Gaussian Splatting},
  author = {Abhishek Saroha and Florian Hofherr and Mariia Gladkova and Cecilia Curreli and Or Litany and Daniel Cremers},
  year = {2025},
  venue = {Preprint},
  eprint = {2501.03875},
  archiveprefix = {arXiv},
  primaryclass = {cs.CV},
  url = {https://arxiv.org/abs/2501.03875},
  image = {./OL_files/teaser_zdyss.png},
  paper = {https://arxiv.org/abs/2501.03875}
}
Epi-NAF: Enhancing Neural Attenuation Fields for Limited-Angle CT with Epipolar Consistency Conditions

Epi-NAF: Enhancing Neural Attenuation Fields for Limited-Angle CT with Epipolar Consistency Conditions

Daniel Gilo, Tzofi Klinghoffer, Or Litany

ISBI 2025Oral

paper /
@article{gilo2024epi,
  title = {Epi-NAF: Enhancing Neural Attenuation Fields for Limited-Angle CT with Epipolar Consistency Conditions},
  author = {Gilo, Daniel and Klinghoffer, Tzofi and Litany, Or},
  year = {2024},
  venue = {ISBI 2025},
  journal = {arXiv preprint arXiv:2411.06181},
  image = {./OL_files/epinaf_teaser.png},
  paper = {https://arxiv.org/abs/2411.06181v1},
  award = {Oral}
}

2024

ReHub: Linear Complexity Graph Transformers with Adaptive Hub-Spoke Reassignment

ReHub: Linear Complexity Graph Transformers with Adaptive Hub-Spoke Reassignment

Tomer Borreda, Daniel Freedman, Or Litany

TMLR

paper / page /
@misc{borreda2024rehublinearcomplexitygraph,
  title = {ReHub: Linear Complexity Graph Transformers with Adaptive Hub-Spoke Reassignment},
  author = {Tomer Borreda and Daniel Freedman and Or Litany},
  year = {2024},
  venue = {TMLR},
  eprint = {2412.01519},
  archiveprefix = {arXiv},
  primaryclass = {cs.LG},
  url = {https://arxiv.org/abs/2412.01519},
  image = {./OL_files/rehub.png},
  paper = {https://arxiv.org/abs/2412.01519},
  page = {https://tomerborreda.github.io/rehub/}
}
Robust Symmetry Detection via Riemannian Langevin Dynamics

Robust Symmetry Detection via Riemannian Langevin Dynamics

Jihyeon Je, Jiayi Liu, Guandao Yang, Boyang Deng, Shengqu Cai, Gordon Wetzstein, Or Litany, Leonidas Guibas

SIGGRAPH-ASIA 2024

paper / page /
@article{je2024robustlangsym,
  title = {Robust Symmetry Detection via Riemannian Langevin Dynamics},
  author = {Jihyeon Je and Jiayi Liu and Guandao Yang and Boyang Deng and Shengqu Cai and Gordon Wetzstein and Or Litany and Leonidas Guibas},
  year = {2024},
  venue = {SIGGRAPH-ASIA 2024},
  journal = {ACM Trans. Graph.},
  eprint = {arXiv:2410.02786},
  doi = {10.1145/3680528.3687682},
  image = {./OL_files/symmetry_teaser.jpg},
  paper = {https://arxiv.org/abs/2410.02786},
  page = {https://symmetry-langevin.github.io/}
}
Zero-to-Hero: Enhancing Zero-Shot Novel View Synthesis via Attention Map Filtering

Zero-to-Hero: Enhancing Zero-Shot Novel View Synthesis via Attention Map Filtering

Ido Sobol, Chenfeng Xu, Or Litany

NeurIPS 2024

paper / page / tweet /
@misc{sobol2024zerotohero,
  title = {Zero-to-Hero: Enhancing Zero-Shot Novel View Synthesis via Attention Map Filtering},
  author = {Ido Sobol and Chenfeng Xu and Or Litany},
  year = {2024},
  venue = {NeurIPS 2024},
  journal = {NeurIPS},
  image = {./OL_files/zero2hero.jpg},
  paper = {https://arxiv.org/abs/2405.18677},
  page = {https://zero2hero-nvs.github.io/},
  tweet = {https://x.com/orlitany/status/1840155773029986480}
}
The NeRFect Match: Exploring NeRF Features for Visual Localization

The NeRFect Match: Exploring NeRF Features for Visual Localization

Qunjie Zhou, Maxim Maximov, Or Litany, Laura Leal-Taixé

ECCV 2024

paper / page /
@misc{zhou2024nerfect,
  title = {The NeRFect Match: Exploring NeRF Features for Visual Localization},
  author = {Qunjie Zhou and Maxim Maximov and Or Litany and Laura Leal-Taixé},
  year = {2024},
  venue = {ECCV 2024},
  journal = {ECCV},
  image = {./OL_files/nerfmatch_teaser.jpg},
  paper = {https://arxiv.org/abs/2403.09577},
  page = {https://nerfmatch.github.io/}
}
Dynamic LiDAR Re-simulation using Compositional Neural Fields

Dynamic LiDAR Re-simulation using Compositional Neural Fields

Hanfeng Wu, Xingxing Zuo, Stefan Leutenegger, Or Litany, Konrad Schindler, Shengyu Huang

CVPR 2024

paper / page /
@inproceedings{Wu2023dynfl,
  title = {Dynamic LiDAR Re-simulation using Compositional Neural Fields},
  author = {Wu, Hanfeng and Zuo, Xingxing and Leutenegger, Stefan and Litany, Or and Schindler, Konrad and Huang, Shengyu},
  year = {2024},
  venue = {CVPR 2024},
  booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
  image = {./OL_files/dynfl_teaser.png},
  paper = {https://arxiv.org/abs/2312.05247},
  page = {https://shengyuh.github.io/dynfl/index.html}
}
3DiffTection: 3D Object Detection with Geometry-Aware Diffusion Features

3DiffTection: 3D Object Detection with Geometry-Aware Diffusion Features

Chenfeng Xu, Huan Ling, Sanja Fidler, Or Litany

CVPR 2024

paper / page /
@article{xu20233difftection,
  title = {3DiffTection: 3D Object Detection with Geometry-Aware Diffusion Features},
  author = {Chenfeng Xu and Huan Ling and Sanja Fidler and Or Litany},
  year = {2023},
  venue = {CVPR 2024},
  journal = {CVPR},
  image = {./OL_files/3difftection.png},
  paper = {https://arxiv.org/abs/2311.04391},
  page = {https://research.nvidia.com/labs/toronto-ai/3difftection/}
}
UnScene3D: Unsupervised 3D Instance Segmentation for Indoor Scenes

UnScene3D: Unsupervised 3D Instance Segmentation for Indoor Scenes

David Rozenberszki, Or Litany, Angela Dai

CVPR 2024

paper / page /
@misc{rozenberszki2023unscene3d,
  title = {UnScene3D: Unsupervised 3D Instance Segmentation for Indoor Scenes},
  author = {David Rozenberszki and Or Litany and Angela Dai},
  year = {2023},
  venue = {CVPR 2024},
  journal = {arXiv preprint arXiv:2303.14541},
  image = {./OL_files/unscene3d_teaser.jpeg},
  paper = {https://arxiv.org/abs/2303.14541},
  page = {https://rozdavid.github.io/unscene3d}
}
Approximately Piecewise E(3) Equivariant Point Networks

Approximately Piecewise E(3) Equivariant Point Networks

Matan Atzmon, Jiahui Huang, Francis Williams, Or Litany

ICLR 2024

paper /
@article{atzmon2024approximately,
  title = {Approximately Piecewise {E(3)} Equivariant Point Networks},
  author = {Atzmon, Matan and Huang, Jiahui and Williams, Francis and Litany, Or},
  year = {2024},
  venue = {ICLR 2024},
  journal = {ICLR},
  image = {./OL_files/APEN_teaser.jpg},
  paper = {https://arxiv.org/abs/2402.08529}
}
EmerNeRF: Emergent Spatial-Temporal Scene Decomposition via Self-Supervision

EmerNeRF: Emergent Spatial-Temporal Scene Decomposition via Self-Supervision

Jiawei Yang, Boris Ivanovic, Or Litany, Xinshuo Weng, Seung Wook Kim, Boyi Li, Tong Che, Danfei Xu, Sanja Fidler, Marco Pavone, Yue Wang

ICLR 2024

paper / page /
@article{yang2023emernerf,
  title = {EmerNeRF: Emergent Spatial-Temporal Scene Decomposition via Self-Supervision},
  author = {Jiawei Yang and Boris Ivanovic and Or Litany and Xinshuo Weng and Seung Wook Kim and Boyi Li and Tong Che and Danfei Xu and Sanja Fidler and Marco Pavone and Yue Wang},
  year = {2023},
  venue = {ICLR 2024},
  journal = {arXiv preprint arXiv:2311.02077},
  image = {./OL_files/emerf_overview.png},
  paper = {https://arxiv.org/abs/2311.02077},
  page = {https://emernerf.github.io/}
}
STMC: Multi-Track Timeline Control for Text-Driven 3D Human Motion Generation

STMC: Multi-Track Timeline Control for Text-Driven 3D Human Motion Generation

Mathis Petrovich, Or Litany, Umar Iqbal, Michael J. Black, Gül Varol, Xue Bin Peng, Davis Rempe

CVPR 2024 Workshop on Human Motion Generation

paper / page /
@article{petrovich24stmc,
  title = {{STMC}: Multi-Track Timeline Control for Text-Driven 3D Human Motion Generation},
  author = {Petrovich, Mathis and Litany, Or and Iqbal, Umar and Black, Michael J. and Varol, G{\"u}l and Peng, Xue Bin and Rempe, Davis},
  year = {2024},
  venue = {CVPR 2024 Workshop on Human Motion Generation},
  journal = {arXiv:2401.08559},
  image = {./OL_files/multitrack_teaser.png},
  paper = {https://arxiv.org/abs/2401.08559},
  page = {https://mathis.petrovich.fr/stmc/}
}

2023

Semi-Supervised Semantic Segmentation via Marginal Contextual Information

Semi-Supervised Semantic Segmentation via Marginal Contextual Information

Moshe Kimhi, Shai Kimhi, Evgenii Zheltonozhskii, Or Litany, Chaim Baskin

TMLR

paper / page /
@article{kimhi2023semisupervised,
  title = {Semi-Supervised Semantic Segmentation via Marginal Contextual Information},
  author = {Moshe Kimhi and Shai Kimhi and Evgenii Zheltonozhskii and Or Litany and Chaim Baskin},
  year = {2023},
  venue = {TMLR},
  eprint = {2308.13900},
  archiveprefix = {arXiv},
  primaryclass = {cs.CV},
  image = {./OL_files/s4mc_teaser.png},
  paper = {https://arxiv.org/abs/2308.13900},
  page = {https://s4mcontext.github.io/}
}
Neural LiDAR Fields for Novel View Synthesis

Neural LiDAR Fields for Novel View Synthesis

Shengyu Huang, Zan Gojcic, Zian Wang, Francis Williams, Yoni Kasten, Sanja Fidler, Konrad Schindler, Or Litany

ICCV 2023

paper / page /
@article{Huang2023nfl,
  title = {Neural LiDAR Fields for Novel View Synthesis},
  author = {Huang, Shengyu and Gojcic, Zan and Wang, Zian and Williams, Francis and Kasten, Yoni and Fidler, Sanja and Schindler, Konrad and Litany, Or},
  year = {2023},
  venue = {ICCV 2023},
  journal = {arXiv preprint},
  image = {./OL_files/nfl_teaser.png},
  paper = {https://arxiv.org/abs/2305.01643},
  page = {https://research.nvidia.com/labs/toronto-ai/nfl/}
}
Towards Viewpoint Robustness in Bird’s Eye View Segmentation

Towards Viewpoint Robustness in Bird’s Eye View Segmentation

Tzofi Klinghoffer, Jonah Philion, Wenzheng Chen, Or Litany, Zan Gojcic, Jungseock Joo, Ramesh Raskar, Sanja Fidler, Jose Alvarez

ICCV 2023

paper / page / talk /
@article{tzofi2023view,
  title = {Towards Viewpoint Robustness in Bird’s Eye View Segmentation},
  author = {Klinghoffer, Tzofi and Philion, Jonah and Chen, Wenzheng and Litany, Or and Gojcic, Zan and Joo, Jungseock and Raskar, Ramesh and Fidler, Sanja and Alvarez, Jose},
  year = {2023},
  venue = {ICCV 2023},
  journal = {ICCV},
  image = {./OL_files/viewrobust_teaser.jpg},
  paper = {https://arxiv.org/pdf/2309.05192.pdf},
  page = {https://nvlabs.github.io/viewpoint-robustness/},
  talk = {https://youtu.be/CuJ9gfJpfhc}
}
Neural Kernel Surface Reconstruction

Neural Kernel Surface Reconstruction

Jiahui Huang, Zan Gojcic, Matan Atzmon, Or Litany, Sanja Fidler, Francis Williams

CVPR 2023Highlight (top 10

paper / code / page /
@article{Huang2023nksr,
  title = {Neural Kernel Surface Reconstruction},
  author = {Huang, Jiahui and Gojcic, Zan and Atzmon, Matan and Litany, Or and Fidler, Sanja and Williams, Francis},
  year = {2023},
  venue = {CVPR 2023},
  journal = {CVPR},
  image = {./OL_files/nksr_teaser.jpg},
  paper = {https://arxiv.org/pdf/2305.19590.pdf},
  page = {https://research.nvidia.com/labs/toronto-ai/NKSR/},
  code = {https://github.com/nv-tlabs/nksr},
  award = {Highlight (top 10% of accepted papers)}
}
Trace and Pace: Controllable Pedestrian Animation via Guided Trajectory Diffusion

Trace and Pace: Controllable Pedestrian Animation via Guided Trajectory Diffusion

Davis Rempe, Zhengyi Luo, Xue Bin Peng, Ye Yuan, Kris Kitani, Karsten Kreis, Sanja Fidler, Or Litany

CVPR 2023

paper / page /
@inproceedings{rempeluo2023tracepace,
  title = {Trace and Pace: Controllable Pedestrian Animation via Guided Trajectory Diffusion},
  author = {Rempe, Davis and Luo, Zhengyi and Peng, Xue Bin and Yuan, Ye and Kitani, Kris and Kreis, Karsten and Fidler, Sanja and Litany, Or},
  year = {2023},
  venue = {CVPR 2023},
  booktitle = {Conference on Computer Vision and Pattern Recognition (CVPR)},
  image = {./OL_files/trace_pace_teaser.png},
  paper = {https://nv-tlabs.github.io/trace-pace/docs/trace_and_pace.pdf},
  page = {https://nv-tlabs.github.io/trace-pace/}
}
Fast Monocular Scene Reconstruction with Global-Sparse Local-Dense Grids

Fast Monocular Scene Reconstruction with Global-Sparse Local-Dense Grids

Wei Dong, Chris Choy, Charles Loop, Yuke Zhu, Or Litany, Anima Anandkumar

CVPR 2023

paper / code / page /
@article{dong2023fast,
  title = {Fast Monocular Scene Reconstruction with Global-Sparse Local-Dense Grids},
  author = {Dong, Wei and Choy, Chris and Loop, Charles and Zhu, Yuke and Litany, Or and Anandkumar, Anima},
  year = {2023},
  venue = {CVPR 2023},
  journal = {CVPR},
  image = {./OL_files/fastmono_teaser.png},
  paper = {https://arxiv.org/abs/2305.13220},
  page = {https://research.nvidia.com/labs/toronto-ai/publication/2023_cvpr_monocular/},
  code = {https://dongwei.info/publication/ash-mono/}
}
Mask3D for 3D Semantic Instance Segmentation

Mask3D for 3D Semantic Instance Segmentation

Jonas Schult, Francis Engelmann, Alexander Hermans, Or Litany, Siyu Tang, Bastian Leibe

ICRA 2023

paper / code / page /
@article{schult2023mask3d,
  title = {Mask3D for 3D Semantic Instance Segmentation},
  author = {Schult, Jonas and Engelmann, Francis and Hermans, Alexander and Litany, Or and Tang, Siyu and Leibe, Bastian},
  year = {2023},
  venue = {ICRA 2023},
  booktitle = {International Conference on Robotics and Automation (ICRA)},
  image = {./OL_files/mask3D.png},
  paper = {https://arxiv.org/abs/2210.03105},
  page = {https://jonasschult.github.io/Mask3D/},
  code = {https://github.com/JonasSchult/Mask3D}
}

2022

GET3D: A Generative Model of High Quality 3D Textured Shapes Learned from Images

GET3D: A Generative Model of High Quality 3D Textured Shapes Learned from Images

Jun Gao, Tianchang Shen, Zian Wang, Wenzheng Chen, Kangxue Yin, Daiqing Li, Or Litany, Zan Gojcic, Sanja Fidler

NeurIPS 2022

paper / code / page /
@inproceedings{gao2022get3d,
  title = {{GET3D}: A Generative Model of High Quality {3D} Textured Shapes Learned from Images},
  author = {Gao, Jun and Shen, Tianchang and Wang, Zian and Chen, Wenzheng and Yin, Kangxue and Li, Daiqing and Litany, Or and Gojcic, Zan and Fidler, Sanja},
  year = {2022},
  venue = {NeurIPS 2022},
  booktitle = {Advances In Neural Information Processing Systems},
  image = {./OL_files/get3D_model.png},
  paper = {https://arxiv.org/abs/2209.11163},
  page = {https://nv-tlabs.github.io/GET3D/},
  code = {https://github.com/nv-tlabs/GET3D}
}
LION: Latent Point Diffusion Models for 3D Shape Generation

LION: Latent Point Diffusion Models for 3D Shape Generation

Xiaohui Zeng, Arash Vahdat, Francis Williams, Zan Gojcic, Or Litany, Sanja Fidler, Karsten Kreis

NeurIPS 2022

paper / code / page /
@article{zeng2022lion,
  title = {LION: Latent Point Diffusion Models for 3D Shape Generation},
  author = {Zeng, Xiaohui and Vahdat, Arash and Williams, Francis and Gojcic, Zan and Litany, Or and Fidler, Sanja and Kreis, Karsten},
  year = {2022},
  venue = {NeurIPS 2022},
  journal = {Advances in Neural Information Processing Systems (NeurIPS)},
  image = {./OL_files/lion_pipeline.jpeg},
  paper = {https://arxiv.org/abs/2210.06978},
  page = {https://nv-tlabs.github.io/LION/},
  code = {https://github.com/nv-tlabs/LION}
}
Language-Grounded Indoor 3D Semantic Segmentation in the Wild

Language-Grounded Indoor 3D Semantic Segmentation in the Wild

David Rozenberszki, Or Litany, Angela Dai

ECCV 2022

paper / code / page /
@article{rozenberszki2022language,
  title = {Language-Grounded Indoor 3D Semantic Segmentation in the Wild},
  author = {Rozenberszki, David and Litany, Or and Dai, Angela},
  year = {2022},
  venue = {ECCV 2022},
  journal = {ECCV},
  image = {./OL_files/scannet200_teaser.jpeg},
  paper = {https://arxiv.org/abs/2204.07761},
  page = {https://rozdavid.github.io/scannet200},
  code = {https://github.com/RozDavid/LanguageGroundedSemseg}
}
MvDeCor: Multi-view Dense Correspondence Learning for Fine-grained 3D Segmentation

MvDeCor: Multi-view Dense Correspondence Learning for Fine-grained 3D Segmentation

Gopal Sharma, Kangxue Yin, Subhransu Maji, Evangelos Kalogerakis, Or Litany, Sanja Fidler

ECCV 2022

paper / code / page /
@article{sharma2022mvdecor,
  title = {MvDeCor: Multi-view Dense Correspondence Learning for Fine-grained 3D Segmentation},
  author = {Sharma, Gopal and Yin, Kangxue and Maji, Subhransu and Kalogerakis, Evangelos and Litany, Or and Fidler, Sanja},
  year = {2022},
  venue = {ECCV 2022},
  journal = {ECCV},
  image = {./OL_files/mvdecor_teaser.png},
  paper = {https://arxiv.org/abs/2208.08580},
  page = {https://nv-tlabs.github.io/MvDeCor/},
  code = {https://github.com/nv-tlabs/MvDeCor}
}
Learning Smooth Neural Functions via Lipschitz Regularization

Learning Smooth Neural Functions via Lipschitz Regularization

Hsueh-Ti Derek Liu, Francis Williams, Alec Jacobson, Sanja Fidler, Or Litany

SIGGRAPH 2022

paper / code / page /
@inproceedings{liu2022learning,
  title = {Learning Smooth Neural Functions via {Lipschitz} Regularization},
  author = {Liu, Hsueh-Ti Derek and Williams, Francis and Jacobson, Alec and Fidler, Sanja and Litany, Or},
  year = {2022},
  venue = {SIGGRAPH 2022},
  booktitle = {ACM SIGGRAPH 2022 Conference Proceedings},
  pages = {1--13},
  image = {./OL_files/lipschitz_teaser.png},
  paper = {https://arxiv.org/abs/2202.08345},
  page = {https://nv-tlabs.github.io/lip-mlp/},
  code = {https://github.com/ml-for-gp/jaxgptoolbox/tree/main/demos/lipschitz_mlp}
}
Federated Learning with Heterogeneous Architectures using Graph HyperNetworks

Federated Learning with Heterogeneous Architectures using Graph HyperNetworks

Or Litany, Haggai Maron, David Acuna, Jan Kautz, Gal Chechik, Sanja Fidler

Preprint

paper /
@article{litany2022federated,
  title = {Federated Learning with Heterogeneous Architectures using Graph {HyperNetworks}},
  author = {Litany, Or and Maron, Haggai and Acuna, David and Kautz, Jan and Chechik, Gal and Fidler, Sanja},
  year = {2022},
  venue = {Preprint},
  journal = {arXiv preprint arXiv:2201.08459},
  image = {./OL_files/heterofl.png},
  paper = {https://arxiv.org/abs/2201.08459}
}
Learning Spectral Unions of Partial Deformable 3D Shapes

Learning Spectral Unions of Partial Deformable 3D Shapes

Luca Moschella, Simone Melzi, Luca Cosmo, Filippo Maggioli, Or Litany, Maks Ovsjanikov, Leonidas Guibas, Emanuele Rodolà

Eurographics 2022

paper /
@inproceedings{moschella2022learning,
  title = {Learning Spectral Unions of Partial Deformable 3D Shapes},
  author = {Moschella, Luca and Melzi, Simone and Cosmo, Luca and Maggioli, Filippo and Litany, Or and Ovsjanikov, Maks and Guibas, Leonidas and Rodol{\`a}, Emanuele},
  year = {2022},
  venue = {Eurographics 2022},
  booktitle = {Computer Graphics Forum},
  volume = {41},
  pages = {407--417},
  image = {./OL_files/spectral_unions_teaser.png},
  paper = {https://arxiv.org/abs/2104.00514},
  number = {2}
}
Generating Useful Accident-Prone Driving Scenarios via a Learned Traffic Prior

Generating Useful Accident-Prone Driving Scenarios via a Learned Traffic Prior

Davis Rempe, Jonah Philion, Leonidas J. Guibas, Sanja Fidler, Or Litany

CVPR 2022

paper / code / page /
@article{rempe2022generating,
  title = {Generating Useful Accident-Prone Driving Scenarios via a Learned Traffic Prior},
  author = {Rempe, Davis and Philion, Jonah and Guibas, Leonidas J. and Fidler, Sanja and Litany, Or},
  year = {2022},
  venue = {CVPR 2022},
  journal = {CVPR},
  image = {./OL_files/strive_teaser.png},
  paper = {https://arxiv.org/abs/2112.05077},
  page = {https://nv-tlabs.github.io/STRIVE/},
  code = {https://github.com/nv-tlabs/STRIVE}
}
Neural Fields as Learnable Kernels for 3D Reconstruction

Neural Fields as Learnable Kernels for 3D Reconstruction

Francis Williams*, Zan Gojcic*, Sameh Khamis, Denis Zorin, Joan Bruna, Sanja Fidler, Or Litany

CVPR 2022

paper / page /
@article{williams2021neural,
  title = {Neural Fields as Learnable Kernels for 3D Reconstruction},
  author = {Williams, Francis and Gojcic, Zan and Khamis, Sameh and Zorin, Denis and Bruna, Joan and Fidler, Sanja and Litany, Or},
  equalcontrib = {1, 2},
  year = {2022},
  venue = {CVPR 2022},
  journal = {CVPR},
  image = {./OL_files/NKF_teaser.png},
  paper = {https://arxiv.org/abs/2111.13674},
  page = {https://nv-tlabs.github.io/nkf/}
}
Neural Fields in Visual Computing and Beyond

Neural Fields in Visual Computing and Beyond

Yiheng Xie, Towaki Takikawa, Shunsuke Saito, Or Litany, Shiqin Yan, Numair Khan, Federico Tombari, James Tompkin, Vincent Sitzmann, Srinath Sridhar

Eurographics 2022 STAR

paper / page /
@inproceedings{xie2022neural,
  title = {Neural Fields in Visual Computing and Beyond},
  author = {Xie, Yiheng and Takikawa, Towaki and Saito, Shunsuke and Litany, Or and Yan, Shiqin and Khan, Numair and Tombari, Federico and Tompkin, James and Sitzmann, Vincent and Sridhar, Srinath},
  year = {2022},
  venue = {Eurographics 2022 STAR},
  booktitle = {Computer Graphics Forum},
  volume = {41},
  pages = {641--676},
  image = {./OL_files/neural_fields_review_teaser.png},
  paper = {https://arxiv.org/abs/2111.11426},
  page = {https://neuralfields.cs.brown.edu/},
  number = {2}
}
Contrast to Divide: Self-Supervised Pre-Training for Learning with Noisy Labels

Contrast to Divide: Self-Supervised Pre-Training for Learning with Noisy Labels

Evgenii Zheltonozhskii, Chaim Baskin, Avi Mendelson, Alex M. Bronstein, Or Litany

WACV 2022

paper /
@article{zheltonozhskii2021contrast,
  title = {Contrast to Divide: Self-Supervised Pre-Training for Learning with Noisy Labels},
  author = {Zheltonozhskii, Evgenii and Baskin, Chaim and Mendelson, Avi and Bronstein, Alex M. and Litany, Or},
  year = {2021},
  venue = {WACV 2022},
  journal = {WACV 2022},
  image = {./OL_files/C2D_teaser.png},
  paper = {https://arxiv.org/abs/2103.13646}
}

2021

DIB-R++: Learning to Predict Lighting and Material with a Hybrid Differentiable Renderer

DIB-R++: Learning to Predict Lighting and Material with a Hybrid Differentiable Renderer

Wenzheng Chen, Joey Litalien, Jun Gao, Zian Wang, Clement Fuji Tsang, Sameh Khamis, Or Litany, Sanja Fidler

NeurIPS 2021

paper / page /
@article{chen2021dib,
  title = {DIB-R++: Learning to Predict Lighting and Material with a Hybrid Differentiable Renderer},
  author = {Chen, Wenzheng and Litalien, Joey and Gao, Jun and Wang, Zian and Tsang, Clement Fuji and Khamis, Sameh and Litany, Or and Fidler, Sanja},
  year = {2021},
  venue = {NeurIPS 2021},
  journal = {Advances in Neural Information Processing Systems (NeurIPS)},
  image = {./OL_files/dibrplus_teaser.png},
  paper = {https://arxiv.org/abs/2111.00140},
  page = {https://nv-tlabs.github.io/DIBRPlus/}
}
Mix3D: Out-of-Context Data Augmentation for 3D Scenes

Mix3D: Out-of-Context Data Augmentation for 3D Scenes

Alexey Nekrasov, Jonas Schult, Or Litany, Bastian Leibe, Francis Engelmann

3DV 2021

paper / page /
@article{nekrasov2021mix3d,
  title = {Mix3D: Out-of-Context Data Augmentation for 3D Scenes},
  author = {Nekrasov, Alexey and Schult, Jonas and Litany, Or and Leibe, Bastian and Engelmann, Francis},
  year = {2021},
  venue = {3DV 2021},
  journal = {3DV 2021},
  image = {./OL_files/mix3d_teaser.png},
  paper = {https://arxiv.org/abs/2110.02210},
  page = {https://kumuji.github.io/mix3d/}
}
StrobeNet: Category-Level Multiview Reconstruction of Articulated Objects

StrobeNet: Category-Level Multiview Reconstruction of Articulated Objects

Ge Zhang, Or Litany, Srinath Sridhar, Leonidas Guibas

Preprint

paper / page /
@article{zhang2021strobenet,
  title = {{StrobeNet}: Category-Level Multiview Reconstruction of Articulated Objects},
  author = {Zhang, Ge and Litany, Or and Sridhar, Srinath and Guibas, Leonidas},
  year = {2021},
  venue = {Preprint},
  journal = {arXiv preprint arXiv:2105.08016},
  image = {./OL_files/strobenet.png},
  paper = {https://arxiv.org/abs/2105.08016},
  page = {https://dzhange.github.io/StrobeNet/}
}
Vector Neurons: A General Framework for SO(3)-Equivariant Networks

Vector Neurons: A General Framework for SO(3)-Equivariant Networks

Congyue Deng, Or Litany, Yueqi Duan, Adrien Poulenard, Andrea Tagliasacchi, Leonidas Guibas

ICCV 2021

paper /
@article{deng2021vector,
  title = {Vector Neurons: A General Framework for {SO(3)}-Equivariant Networks},
  author = {Deng, Congyue and Litany, Or and Duan, Yueqi and Poulenard, Adrien and Tagliasacchi, Andrea and Guibas, Leonidas},
  year = {2021},
  venue = {ICCV 2021},
  journal = {ICCV 2021},
  image = {./OL_files/VNN_teaser.png},
  paper = {https://arxiv.org/abs/2104.12229}
}
ReLMoGen: Integrating Motion Generation in Reinforcement Learning for Mobile Manipulation

ReLMoGen: Integrating Motion Generation in Reinforcement Learning for Mobile Manipulation

Fei Xia, Chengshu Li, Roberto Martı́n-Martı́n, Or Litany, Alexander Toshev, Silvio Savarese

ICRA 2021

paper / talk /
@inproceedings{xia2021relmogen,
  title = {{ReLMoGen}: Integrating Motion Generation in Reinforcement Learning for Mobile Manipulation},
  author = {Xia, Fei and Li, Chengshu and Mart{\'\i}n-Mart{\'\i}n, Roberto and Litany, Or and Toshev, Alexander and Savarese, Silvio},
  year = {2021},
  venue = {ICRA 2021},
  booktitle = {2021 IEEE International Conference on Robotics and Automation (ICRA)},
  pages = {4583--4590},
  image = {./OL_files/relmogen_teaser.png},
  paper = {https://arxiv.org/abs/2008.07792},
  talk = {https://youtu.be/mTaJ9xQMiD0?t=2083},
  organization = {IEEE}
}
Weakly Supervised Learning of Rigid 3D Scene Flow

Weakly Supervised Learning of Rigid 3D Scene Flow

Zan Gojcic, Or Litany, Andreas Wieser, Leonidas J. Guibas, Tolga Birdal

CVPR 2021

paper / page /
@article{gojcic2021weakly,
  title = {Weakly Supervised Learning of Rigid 3D Scene Flow},
  author = {Gojcic, Zan and Litany, Or and Wieser, Andreas and Guibas, Leonidas J. and Birdal, Tolga},
  year = {2021},
  venue = {CVPR 2021},
  journal = {CVPR 2021},
  image = {./OL_files/weakly_cvpr21.png},
  paper = {https://arxiv.org/abs/2102.08945},
  page = {https://3dsceneflow.github.io/}
}
Causal BERT: Improving Object Detection by Searching for Challenging Groups

Causal BERT: Improving Object Detection by Searching for Challenging Groups

Cinjon Resnick, Or Litany, Amlan Kar, Karsten Kreis, James Lucas, Kyunghyun Cho, Sanja Fidler

ICCV workshop

paper /
@inproceedings{resnick2021causal,
  title = {Causal {BERT}: Improving Object Detection by Searching for Challenging Groups},
  author = {Resnick, Cinjon and Litany, Or and Kar, Amlan and Kreis, Karsten and Lucas, James and Cho, Kyunghyun and Fidler, Sanja},
  year = {2021},
  venue = {ICCV workshop},
  booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision},
  pages = {2972--2981},
  image = {./OL_files/causal_scene_bert.jpeg},
  paper = {https://arxiv.org/abs/2202.03651}
}
3DIoUMatch: Leveraging IoU Prediction for Semi-Supervised 3D Object Detection

3DIoUMatch: Leveraging IoU Prediction for Semi-Supervised 3D Object Detection

He Wang*, Yezhen Cong*, Or Litany, Yue Gao, Leonidas J. Guibas

CVPR 2021

paper / page /
@article{wang20203dioumatch,
  title = {3DIoUMatch: Leveraging IoU Prediction for Semi-Supervised 3D Object Detection},
  author = {Wang, He and Cong, Yezhen and Litany, Or and Gao, Yue and Guibas, Leonidas J.},
  equalcontrib = {1, 2},
  year = {2020},
  venue = {CVPR 2021},
  journal = {CVPR 2021},
  image = {./OL_files/3dioumatch.png},
  paper = {https://arxiv.org/abs/2012.04355},
  page = {https://thu17cyz.github.io/3DIoUMatch/}
}
Representation Learning Through Latent Canonicalizations

Representation Learning Through Latent Canonicalizations

Or Litany, Ari Morcos, Srinath Sridhar, Leonidas Guibas, Judy Hoffman

WACV 2021

paper / talk /
@article{litany2020representation,
  title = {Representation Learning Through Latent Canonicalizations},
  author = {Litany, Or and Morcos, Ari and Sridhar, Srinath and Guibas, Leonidas and Hoffman, Judy},
  year = {2020},
  venue = {WACV 2021},
  journal = {WACV 2021},
  image = {./OL_files/canonicalizers.png},
  paper = {https://arxiv.org/abs/2002.11829},
  talk = {https://youtu.be/l1Dh4vHuYQ4}
}
Continuous Geodesic Convolutions for Learning on 3D Shapes

Continuous Geodesic Convolutions for Learning on 3D Shapes

Zhangsihao Yang, Or Litany, Tolga Birdal, Srinath Sridhar, Leonidas Guibas

WACV 2021

paper /
@article{yang2020continuous,
  title = {Continuous Geodesic Convolutions for Learning on 3D Shapes},
  author = {Yang, Zhangsihao and Litany, Or and Birdal, Tolga and Sridhar, Srinath and Guibas, Leonidas},
  year = {2020},
  venue = {WACV 2021},
  journal = {WACV 2021},
  image = {./OL_files/contConv.png},
  paper = {https://arxiv.org/abs/2002.02506}
}

2020

Human 3D keypoints via spatial uncertainty modeling

Human 3D keypoints via spatial uncertainty modeling

Francis Williams, Or Litany, Avneesh Sud, Kevin Swersky, Andrea Tagliasacchi

Preprint

paper /
@article{williams2020human,
  title = {Human 3D keypoints via spatial uncertainty modeling},
  author = {Williams, Francis and Litany, Or and Sud, Avneesh and Swersky, Kevin and Tagliasacchi, Andrea},
  year = {2020},
  venue = {Preprint},
  journal = {arXiv preprint arXiv:2012.10518},
  image = {./OL_files/3d_keypoint_estimation.png},
  paper = {https://arxiv.org/abs/2012.10518}
}
Learned Equivariant Rendering without Transformation Supervision

Learned Equivariant Rendering without Transformation Supervision

Cinjon Resnick, Or Litany, Hugo Larochelle, Joan Bruna, Kyunghyun Cho

Neurips 2020 DiffCVGP workshop

paper /
@inproceedings{resnick2020learned,
  title = {Learned Equivariant Rendering without Transformation Supervision},
  author = {Resnick, Cinjon and Litany, Or and Larochelle, Hugo and Bruna, Joan and Cho, Kyunghyun},
  year = {2020},
  venue = {Neurips 2020 DiffCVGP workshop},
  booktitle = {Diffcvgp workshop http://montrealrobotics.ca/diffcvgp/},
  image = {./OL_files/equi_render.png},
  paper = {https://arxiv.org/abs/2011.05787v1}
}
Object-Centric Multi-View Aggregation

Object-Centric Multi-View Aggregation

Shubham Tulsiani, Or Litany, Charles R. Qi, He Wang, Leonidas J. Guibas

Preprint

paper /
@article{tulsiani2020object,
  title = {Object-Centric Multi-View Aggregation},
  author = {Tulsiani, Shubham and Litany, Or and Qi, Charles R. and Wang, He and Guibas, Leonidas J.},
  year = {2020},
  venue = {Preprint},
  journal = {arXiv preprint arXiv:2007.10300},
  image = {./OL_files/mva_teaser.png},
  paper = {http://arxiv.org/abs/2007.10300}
}
PointContrast: Unsupervised Pre-training for 3D Point Cloud Understanding

PointContrast: Unsupervised Pre-training for 3D Point Cloud Understanding

Saining Xie, Jiatao Gu, Demi Guo, Charles R. Qi, Leonidas J. Guibas, Or Litany

ECCV 2020Spotlight

paper /
@inproceedings{xie2020pointcontrast,
  title = {PointContrast: Unsupervised Pre-training for 3D Point Cloud Understanding},
  author = {Xie, Saining and Gu, Jiatao and Guo, Demi and Qi, Charles R. and Guibas, Leonidas J. and Litany, Or},
  year = {2020},
  venue = {ECCV 2020},
  booktitle = {ECCV 2020 Spotlight},
  image = {./OL_files/pointContrast.png},
  paper = {https://arxiv.org/abs/2007.10985},
  award = {Spotlight}
}
Towards Precise Completion of Deformable Shapes

Towards Precise Completion of Deformable Shapes

Oshri Halimi, Ido Imanuel, Or Litany, Giovanni Trappolini, Emanuele Rodolà, Leonidas Guibas, Ron Kimmel

ECCV 2020

paper /
@inproceedings{halimi2020towards,
  title = {Towards Precise Completion of Deformable Shapes},
  author = {Halimi, Oshri and Imanuel, Ido and Litany, Or and Trappolini, Giovanni and Rodol{\`a}, Emanuele and Guibas, Leonidas and Kimmel, Ron},
  year = {2020},
  venue = {ECCV 2020},
  booktitle = {Computer Vision--ECCV 2020: 16th European Conference, Glasgow, UK, August 23--28, 2020, Proceedings, Part XXIV 16},
  pages = {359--377},
  image = {./OL_files/theWhole.png},
  paper = {https://arxiv.org/abs/2001.09650},
  organization = {Springer International Publishing}
}
On Learning Sets of Symmetric Elements

On Learning Sets of Symmetric Elements

Haggai Maron, Or Litany, Gal Chechik, Ethan Fetaya

ICML 2020Outstanding Paper Award

paper /
@inproceedings{maron2020learning,
  title = {On Learning Sets of Symmetric Elements},
  author = {Maron, Haggai and Litany, Or and Chechik, Gal and Fetaya, Ethan},
  year = {2020},
  venue = {ICML 2020},
  booktitle = {ICML 2020 -- Outstanding paper award},
  image = {./OL_files/dss_layer.png},
  paper = {https://arxiv.org/abs/2002.08599},
  award = {Outstanding Paper Award}
}
ImVoteNet: Boosting 3D Object Detection in Point Clouds with Image Votes

ImVoteNet: Boosting 3D Object Detection in Point Clouds with Image Votes

Charles R. Qi, Xinlei Chen, Or Litany, Leonidas J. Guibas

CVPR 2020

paper / talk /
@inproceedings{qi2020imvotenet,
  title = {ImVoteNet: Boosting 3D Object Detection in Point Clouds with Image Votes},
  author = {Qi, Charles R. and Chen, Xinlei and Litany, Or and Guibas, Leonidas J.},
  year = {2020},
  venue = {CVPR 2020},
  booktitle = {CVPR 2020},
  image = {./OL_files/imvote.png},
  paper = {https://arxiv.org/abs/2001.10692},
  talk = {https://www.youtube.com/watch?v=xCnbvgMAg-Y}
}

2019

Deep Hough Voting for 3D Object Detection in Point Clouds

Deep Hough Voting for 3D Object Detection in Point Clouds

Charles R. Qi, Or Litany, Kaiming He, Leonidas J. Guibas

ICCV, 2019Best Paper Nomination

paper / code / slides / talk /
@inproceedings{qi2019deep,
  title = {Deep Hough Voting for 3D Object Detection in Point Clouds},
  author = {Qi, Charles R. and Litany, Or and He, Kaiming and Guibas, Leonidas J.},
  year = {2019},
  venue = {ICCV, 2019},
  booktitle = {ICCV 2019 (Oral, Best Paper Nomination)},
  image = {./OL_files/DHV_teaser.png},
  paper = {https://arxiv.org/pdf/1904.09664.pdf},
  code = {https://github.com/facebookresearch/votenet},
  slides = {./OL_files/talks/deep_hough_voting.pdf},
  talk = {https://youtu.be/2ntDYowHbZs?t=4585},
  award = {Best Paper Nomination}
}
Dual-primal graph convolutional networks

Dual-primal graph convolutional networks

Federico Monti, Oleksandr Shchur, Aleksandar Bojchevski, Or Litany, Stephan Günnemann, Michael M. Bronstein

GEM workshop at ECML-PKDD, 2019Oral presentation

paper /
@article{monti2018dual,
  title = {Dual-primal graph convolutional networks},
  author = {Monti, Federico and Shchur, Oleksandr and Bojchevski, Aleksandar and Litany, Or and G{\"u}nnemann, Stephan and Bronstein, Michael M.},
  year = {2018},
  venue = {GEM workshop at ECML-PKDD, 2019},
  journal = {arXiv preprint arXiv:1806.00770},
  image = {./OL_files/dualprimal.png},
  paper = {https://arxiv.org/pdf/1806.00770.pdf},
  award = {Oral presentation}
}
SOSELETO: A Unified Approach to Transfer Learning and Training with Noisy Labels

SOSELETO: A Unified Approach to Transfer Learning and Training with Noisy Labels

Or Litany, Daniel Freedman

ICLR workshop on Learning from Limited Labeled Data, 2019Best Paper Award

paper / code / slides / poster / talk /
@inproceedings{litany2019soseleto,
  title = {SOSELETO: A Unified Approach to Transfer Learning and Training with Noisy Labels},
  author = {Litany, Or and Freedman, Daniel},
  year = {2019},
  venue = {ICLR workshop on Learning from Limited Labeled Data, 2019},
  booktitle = {ICLR workshop on Learning from Limited Labeled Data (LLD) -- Best Paper Award},
  image = {./OL_files/soseleto.png},
  paper = {https://arxiv.org/pdf/1805.09622.pdf},
  code = {https://github.com/orlitany/SOSELETO},
  slides = {./OL_files/SOSELETO_presentation.pdf},
  poster = {./OL_files/SOSELETO_ICLR19_poster.pdf},
  talk = {https://slideslive.com/38915746},
  award = {Best Paper Award}
}
Unsupervised Learning of Dense Shape Correspondence

Unsupervised Learning of Dense Shape Correspondence

Oshri Halimi, Or Litany, Emanuele Rodolà, Alex M. Bronstein, Ron Kimmel

Computer Vision and Pattern Recognition (CVPR), 2019Oral presentation

paper / code / talk /
@inproceedings{halimi2019unsupervised,
  title = {Unsupervised Learning of Dense Shape Correspondence},
  author = {Halimi, Oshri and Litany, Or and Rodol{\`a}, Emanuele and Bronstein, Alex M. and Kimmel, Ron},
  year = {2019},
  venue = {Computer Vision and Pattern Recognition (CVPR), 2019},
  booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  pages = {4370--4379},
  image = {./OL_files/unsupervised_fmnet.png},
  paper = {https://arxiv.org/pdf/1812.02415.pdf},
  code = {https://github.com/OshriHalimi/unsupervised_learning_of_dense_shape_correspondence},
  talk = {https://www.linkedin.com/feed/update/urn:li:activity:6547910607310598144},
  award = {Oral presentation}
}

2018

Deformable Shape Completion with Graph Convolutional Autoencoders

Deformable Shape Completion with Graph Convolutional Autoencoders

Or Litany, Alex Bronstein, Michael Bronstein, Ameesh Makadia

Computer Vision and Pattern Recognition (CVPR), 2018

paper /
@inproceedings{litany2018deformable,
  title = {Deformable Shape Completion with Graph Convolutional Autoencoders},
  author = {Litany, Or and Bronstein, Alex and Bronstein, Michael and Makadia, Ameesh},
  year = {2018},
  venue = {Computer Vision and Pattern Recognition (CVPR), 2018},
  booktitle = {Proceedings of the IEEE conference on computer vision and pattern recognition},
  pages = {1886--1895},
  image = {./OL_files/shapeComp.png},
  paper = {https://arxiv.org/pdf/1712.00268v1.pdf}
}
Partial Single-and Multishape Dense Correspondence Using Functional Maps

Partial Single-and Multishape Dense Correspondence Using Functional Maps

Or Litany, Emanuele Rodolà, Alex Bronstein, Michael Bronstein, Daniel Cremers

Handbook of Numerical Analysis, Elsevier, 2018

paper /
@incollection{litany2018partial,
  title = {Partial Single-and Multishape Dense Correspondence Using Functional Maps},
  author = {Litany, Or and Rodol{\`a}, Emanuele and Bronstein, Alex and Bronstein, Michael and Cremers, Daniel},
  year = {2018},
  venue = {Handbook of Numerical Analysis, Elsevier, 2018},
  booktitle = {Handbook of Numerical Analysis},
  publisher = {Elsevier},
  volume = {19},
  pages = {55--90},
  image = {./OL_files/pfm_book.png},
  paper = {https://www.sciencedirect.com/science/article/pii/S1570865918300097}
}
Class-Aware Fully Convolutional Gaussian and Poisson Denoising

Class-Aware Fully Convolutional Gaussian and Poisson Denoising

Tal Remez, Or Litany, Raja Giryes, Alex M. Bronstein

IEEE Transactions on Image Processing, 2018

paper / code /
@article{remez2018class,
  title = {Class-Aware Fully Convolutional {Gaussian} and {Poisson} Denoising},
  author = {Remez, Tal and Litany, Or and Giryes, Raja and Bronstein, Alex M.},
  year = {2018},
  venue = {IEEE Transactions on Image Processing, 2018},
  journal = {IEEE Transactions on Image Processing},
  publisher = {IEEE},
  volume = {27},
  pages = {5707--5722},
  image = {./OL_files/class_aware_poiss.png},
  paper = {https://arxiv.org/pdf/1808.06562.pdf},
  code = {https://github.com/TalRemez/deep_class_aware_denoising},
  number = {11}
}

2017

Efficient Deformable Shape Correspondence via Kernel Matching

Efficient Deformable Shape Correspondence via Kernel Matching

Zorah Lähner, Matthias Vestner, Amit Boyarski, Or Litany, Ron Slossberg, Tal Remez, Emanuele Rodolà, Alex Bronstein, Michael Bronstein, Ron Kimmel, Daniel Cremers

Intl. Conference on 3D Vision (3DV), 2017

paper / code /
@article{lahner2017efficient,
  title = {Efficient Deformable Shape Correspondence via Kernel Matching},
  author = {L{\"a}hner, Zorah and Vestner, Matthias and Boyarski, Amit and Litany, Or and Slossberg, Ron and Remez, Tal and Rodol{\`a}, Emanuele and Bronstein, Alex and Bronstein, Michael and Kimmel, Ron and Cremers, Daniel},
  year = {2017},
  venue = {Intl. Conference on 3D Vision (3DV), 2017},
  journal = {3DV},
  image = {./OL_files/vestner-3dv17.png},
  paper = {https://arxiv.org/pdf/1707.08991.pdf},
  code = {https://github.com/zorah/KernelMatching}
}
Deep Functional Maps: Structured Prediction for Dense Shape Correspondence

Deep Functional Maps: Structured Prediction for Dense Shape Correspondence

Or Litany, Tal Remez, Emanuele Rodolà, Alex Bronstein, Michael Bronstein

ICCV, 2017

paper / code /
@inproceedings{litany2017deep,
  title = {Deep Functional Maps: Structured Prediction for Dense Shape Correspondence},
  author = {Litany, Or and Remez, Tal and Rodol{\`a}, Emanuele and Bronstein, Alex and Bronstein, Michael},
  year = {2017},
  venue = {ICCV, 2017},
  booktitle = {Proceedings of the IEEE international conference on computer vision},
  pages = {5659--5667},
  image = {./OL_files/FMNet.png},
  paper = {http://vision.in.tum.de/_media/spezial/bib/litany-iccv17.pdf},
  code = {https://github.com/orlitany/DeepFunctionalMaps}
}
Deep Class-Aware Image Denoising

Deep Class-Aware Image Denoising

Tal Remez, Or Litany, Raja Giryes, Alex M. Bronstein

IEEE International Conference on Image Processing (ICIP), 2017

paper / code /
@inproceedings{remez2017deep,
  title = {Deep Class-Aware Image Denoising},
  author = {Remez, Tal and Litany, Or and Giryes, Raja and Bronstein, Alex M.},
  year = {2017},
  venue = {IEEE International Conference on Image Processing (ICIP), 2017},
  booktitle = {2017 international conference on sampling theory and applications (SampTA)},
  pages = {138--142},
  image = {./OL_files/clsawrden.png},
  paper = {https://arxiv.org/abs/1701.01698},
  code = {https://github.com/TalRemez/deep_class_aware_denoising},
  organization = {IEEE}
}
Cloud Dictionary: Sparse Coding and Modeling for Point Clouds

Cloud Dictionary: Sparse Coding and Modeling for Point Clouds

Or Litany*, Tal Remez*, Alex Bronstein

Signal Processing with Adaptive Sparse Structured Representations (SPARS), 2017

paper /
@article{litany2017cloud,
  title = {Cloud Dictionary: Sparse Coding and Modeling for Point Clouds},
  author = {Litany, Or and Remez, Tal and Bronstein, Alex},
  equalcontrib = {1, 2},
  year = {2017},
  venue = {Signal Processing with Adaptive Sparse Structured Representations (SPARS), 2017},
  journal = {SPARS},
  image = {./OL_files/clouddict.png},
  paper = {https://arxiv.org/pdf/1612.04956v1}
}
Fully Spectral Partial Shape Matching

Fully Spectral Partial Shape Matching

Or Litany, Emanuele Rodolà, Alex M. Bronstein, Michael M. Bronstein

Computer Graphics Forum, Vol. 36(2), 2017Presented at Eurographics, 2017

paper / code /
@inproceedings{litany2017fully,
  title = {Fully Spectral Partial Shape Matching},
  author = {Litany, Or and Rodol{\`a}, Emanuele and Bronstein, Alex M. and Bronstein, Michael M.},
  year = {2017},
  venue = {Computer Graphics Forum, Vol. 36(2), 2017},
  booktitle = {Computer Graphics Forum},
  volume = {36},
  image = {./OL_files/fullyspectral.png},
  paper = {http://vision.in.tum.de/_media/spezial/bib/litany-eg17.pdf},
  code = {https://github.com/orlitany/FSPM},
  award = {Presented at Eurographics, 2017},
  number = {2},
  organization = {The Eurographics Association and John Wiley \& Sons Ltd.}
}
SHREC’17: Deformable Shape Retrieval with Missing Parts

SHREC’17: Deformable Shape Retrieval with Missing Parts

Emanuele Rodolà, Luca Cosmo, Or Litany, Michael M. Bronstein, Alex M. Bronstein, et al.

EUROGRAPHICS Workshop on 3D Object Retrieval (3DOR), 2017

paper / code / dataset /
@inproceedings{rodola2017shrec,
  title = {{SHREC}’17: Deformable Shape Retrieval with Missing Parts},
  author = {Rodol{\`a}, Emanuele and Cosmo, Luca and Litany, Or and Bronstein, Michael M. and Bronstein, Alex M. and others},
  year = {2017},
  venue = {EUROGRAPHICS Workshop on 3D Object Retrieval (3DOR), 2017},
  booktitle = {Proceedings of the Eurographics Workshop on 3D Object Retrieval, Lisbon, Portugal},
  pages = {23--24},
  image = {./OL_files/shrec17.png},
  paper = {http://vision.in.tum.de/_media/spezial/bib/shrec17partial.pdf},
  code = {http://vision.in.tum.de/_media/spezial/bib/shrec17-baseline.zip},
  dataset = {https://sites.google.com/view/shrec17/}
}
ASIST: Automatic Semantically Invariant Scene Transformation

ASIST: Automatic Semantically Invariant Scene Transformation

Or Litany, Tal Remez, Daniel Freedman, Lior Shapira, Alex Bronstein, Ran Gal

Computer Vision and Image Understanding (CVIU), 2017

paper /
@article{litany2017asist,
  title = {{ASIST}: Automatic Semantically Invariant Scene Transformation},
  author = {Litany, Or and Remez, Tal and Freedman, Daniel and Shapira, Lior and Bronstein, Alex and Gal, Ran},
  year = {2017},
  venue = {Computer Vision and Image Understanding (CVIU), 2017},
  journal = {Computer Vision and Image Understanding},
  publisher = {Academic Press},
  volume = {157},
  pages = {284--299},
  image = {./OL_files/asist.png},
  paper = {http://arxiv.org/abs/1512.01515}
}

2016

Non-Rigid Puzzles

Non-Rigid Puzzles

Or Litany, Emanuele Rodolà, Alex Bronstein, Michael Bronstein, Daniel Cremers

Computer Graphics Forum, Wiley, volume 35, 2016SGP Best Paper Award

paper / code /
@inproceedings{litany2016non,
  title = {Non-Rigid Puzzles},
  author = {Litany, Or and Rodol{\`a}, Emanuele and Bronstein, Alex and Bronstein, Michael and Cremers, Daniel},
  year = {2016},
  venue = {Computer Graphics Forum, Wiley, volume 35, 2016},
  booktitle = {Computer Graphics Forum},
  volume = {35},
  pages = {135--143},
  image = {./OL_files/puzzles.png},
  paper = {http://vision.in.tum.de/_media/spezial/bib/litany16.pdf},
  code = {https://github.com/orlitany/NonRigidPuzzles},
  award = {SGP Best Paper Award},
  number = {5},
  organization = {The Eurographics Association and John Wiley \& Sons Ltd.}
}
A picture is worth a billion bits: Real-time image reconstruction from dense binary threshold pixels

A picture is worth a billion bits: Real-time image reconstruction from dense binary threshold pixels

Tal Remez*, Or Litany*, Alex Bronstein

International Conference on Computational Photography (ICCP), 2016

paper /
@inproceedings{remez2016picture,
  title = {A picture is worth a billion bits: Real-time image reconstruction from dense binary threshold pixels},
  author = {Remez, Tal and Litany, Or and Bronstein, Alex},
  equalcontrib = {1, 2},
  year = {2016},
  venue = {International Conference on Computational Photography (ICCP), 2016},
  booktitle = {2016 IEEE International Conference on Computational Photography (ICCP)},
  pages = {1--9},
  image = {./OL_files/binarycam.png},
  paper = {https://arxiv.org/pdf/1510.04601.pdf},
  organization = {IEEE}
}
FPGA system for real-time computational extended depth of field imaging using phase aperture coding

FPGA system for real-time computational extended depth of field imaging using phase aperture coding

Tal Remez, Or Litany, Shachar Yoseff, Harel Haim, Alex Bronstein

Preprint

paper /
@article{remez2016fpga,
  title = {FPGA system for real-time computational extended depth of field imaging using phase aperture coding},
  author = {Remez, Tal and Litany, Or and Yoseff, Shachar and Haim, Harel and Bronstein, Alex},
  year = {2016},
  venue = {Preprint},
  journal = {arXiv preprint arXiv:1608.01074},
  image = {./OL_files/fpga.png},
  paper = {https://arxiv.org/abs/1608.01074}
}

2015

Image reconstruction from dense binary pixels

Image reconstruction from dense binary pixels

Or Litany*, Tal Remez*, Alex Bronstein

Signal Processing with Adaptive Sparse Structured Representations (SPARS), 2015

paper /
@misc{litany2015image,
  title = {Image reconstruction from dense binary pixels},
  author = {Or Litany and Tal Remez and Alex Bronstein},
  equalcontrib = {1, 2},
  year = {2015},
  venue = {Signal Processing with Adaptive Sparse Structured Representations (SPARS), 2015},
  archiveprefix = {arXiv preprint arXiv:1512.01774},
  image = {./OL_files/binarycamspars.png},
  paper = {http://arxiv.org/abs/1512.01774}
}

2012

Putting the Pieces Together: Regularized Multi-part Shape Matching

Putting the Pieces Together: Regularized Multi-part Shape Matching

Or Litany, Alexander M. Bronstein, Michael M. Bronstein

Workshop on Nonrigid Shape Analysis and Deformable Image Alignment (NORDIA), 2012

paper /
@inproceedings{litany2012putting,
  title = {Putting the Pieces Together: Regularized Multi-part Shape Matching},
  author = {Litany, Or and Bronstein, Alexander M. and Bronstein, Michael M.},
  year = {2012},
  venue = {Workshop on Nonrigid Shape Analysis and Deformable Image Alignment (NORDIA), 2012},
  booktitle = {ECCV Workshops (1)},
  pages = {1--11},
  image = {./OL_files/rigidpuzzles.png},
  paper = {https://vista.cs.technion.ac.il/wp-content/uploads/2018/10/LitBroBroNORDIA12.pdf}
}
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