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GeezerVison is showing x-decoder-vl.github.io — Towards a Generalized Multi-Modal Foundation Model

Towards a Generalized Multimodal Foundation Model

Along the track of X-Decoder, SEEM, and FIND, our goal is to build a foundation model that extendable to a wide range of vision and vision-language tasks without any overhead!

X-Decoder (CVPR 2023)

"Generalized Decoding for Pixel, Image, and Language" [1] shortened as X-Decoder is a generalized decoding system that is applicable to various vision-language tasks with a unified architecture. The input and output modalities spans vision-language while the granularity spans pixel-image.

Code ☆ 1.1k X-GPT

SEEM (NeurIPS 2023)

"Segment Everything Everywhere All-at-Once" [2] denoted as SEEM in extending X-Decoder with human interaction capability, where human can refer a segment with scribble, box, point, and etc. Meanwhile, it accepts prompts span vision-language in a composite manner.

Code ☆ 3.6k Demo

FIND (New!)

"Interfacing Foundation Models' Embeddings" denoted as FIND introduces a generalized interface for foundation models. It aligns an embedding space with interleaved reasoning capability for pretrained-and-fixed foundation models (e.g. X-Decoder, UniCL, SAM, LLaMA).

Code Demo

▶ FIND

FIND interfacing foundation models for an interleaved embedding space.

▶ SEEM

SEEM supports a wide range of prompt types including text, scribble, ref-image, and etc.

▶ X-Deocder

X-Decoder is a single model trained to support a wide range of vision and vision-language tasks.

BibTeX


    @article{zou2023xdecoder,
      author      = {Xueyan Zou*, Zi-Yi Dou*, Jianwei Yang*, Zhe Gan, Linjie Li, Chunyuan Li, Xiyang Dai, Harkirat Behl, Jianfeng Wang, Lu Yuan, Nanyun Peng, Lijuan Wang, Yong Jae Lee*, Jianfeng Gao*},
      title       = {Generalized Decoding for Pixel, Image and Language},
      publisher   = {CVPR},
      year        = {2023},
    }
    @article{zou2023seem,
      author      = {Xueyan Zou*, Jianwei Yang*, Hao Zhang*, Feng Li*, Linjie Li, Jianfeng Wang, Lijuan Wang, Jianfeng Gao*, Yong Jae Lee*},
      title       = {Segment everything everywhere all at once},
      publisher   = {NeurIPS},
      year        = {2023},
    }
    @article{zou2023find,
      author      = {Xueyan Zou, Linjie Li, Jianfeng Wang, Jianwei Yang, Mingyu Ding, Zhengyuan Yang, Feng Li, Hao Zhang, Shilong Liu, Arul Aravinthan, Yong Jae Lee*, Lijuan Wang*},
      title       = {Generalized Decoding for Pixel, Image and Language},
      publisher   = {arXiv},
      year        = {2023},
    }

Acknowledgement

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