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X-modaler is a versatile and high-performance codebase for cross-modal analytics(e.g., image captioning, video captioning, vision-language pre-training, visual question answering, visual commonsense reasoning, and cross-modal retrieval).
image-captioning video-captioning visual-question-answering vision-and-language cross-modal-retrieval pretraining tden
pytorch implementation of video captioning
Video to Text: Natural language description generator for some given video. [Video Captioning]
deep-neural-networks video-processing image-captioning cnn-keras audio-processing lstm-neural-networks video-captioning video-to-text
We introduce temporal working memory (TWM), which aims to enhance the temporal modeling capabilities of Multimodal foundation models (MFMs). This plug-and-play module can be easily integrated into existing MFMs. With our TWM, nine state-of-the-art models exhibit significant performance improvements across QA, captioning, and retrieval tasks.
question-answering video-captioning working-memory audio-visual-learning video-text-retrieval multimodal-large-language-models multimodal-foundation-model
Auto transcribe tool based on whisper
text-to-speech deep-learning pytorch speech-recognition speech-to-text language-model gradio speech-processing asr video-captioning voice-activity-detection gradio-interface
[NeurIPS 2023 D&B] VidChapters-7M: Video Chapters at Scale
video-understanding weakly-supervised-learning video-captioning multimodal-learning vision-and-language dense-video-captioning pre-training temporal-language-grounding video-chapter-generation vid2seq
A new multi-shot video understanding benchmark Shot2Story with comprehensive video summaries and detailed shot-level captions.
benchmark research video-summarization dataset video-captioning video-story vision-language video-question-answering video-language large-language-models video-language-pretraining video-story-generation
[ACL 2020] PyTorch code for MART: Memory-Augmented Recurrent Transformer for Coherent Video Paragraph Captioning
This repository contains the code for a video captioning system inspired by Sequence to Sequence -- Video to Text. This system takes as input a video and generates a caption in English describing the video.
[NeurIPS 2022 Spotlight] Expectation-Maximization Contrastive Learning for Compact Video-and-Language Representations
Machine Learning and having it Deep and Structured (MLDS) in 2018 spring
reinforcement-learning spring chatbot generative-adversarial-network gan policy-gradient seq2seq image-generation sequence-to-sequence chat-bot ntu deep-q-network text-to-image actor-critic video-captioning 2018 chinese-chatbot hung-yi-lee mlds2018spring mlds
Summary about Video-to-Text datasets. This repository is part of the review paper *Bridging Vision and Language from the Video-to-Text Perspective: A Comprehensive Review*
review video-captioning state-of-the-art vision-and-language charades video-to-text msvd video-dataset video-description activitynet-captions trecvid tgif-dataset msr-vtt vatex
ZerolanCore integrates many open-source, locally deployable AI models, and aims to integrate a series of AI models such as large language model (LLM), automatic speech recognition (ASR), text-to-speech (TTS), image captioning, optical character recognition (OCR), video captioning, etc.
A curated list of Multimodal Captioning related research(including image captioning, video captioning, and text captioning)
这是一个基于Pytorch平台、Transformer框架实现的视频描述生成 (Video Captioning) 深度学习模型。 视频描述生成任务指的是：输入一个视频，输出一句描述整个视频内容的文字（前提是视频较短且可以用一句话来描述）。本repo主要目的是帮助视力障碍者欣赏网络视频、感知周围环境，促进“无障碍视频”的发展。
[ECCV 2020] PyTorch code of MMT (a multimodal transformer captioning model) on TVCaption dataset
What and How Well You Performed? A Multitask Learning Approach to Action Quality Assessment [CVPR 2019]
pytorch video-processing lstm representation-learning action-recognition video-understanding c3d video-captioning captioning fine-grained-classification multitask-learning dilated-convolution action-quality-assessment mtl-aqa fine-grained-action-recognition dilated-c3d
A PyTorch implementation of state of the art video captioning models from 2015-2019 on MSVD and MSRVTT datasets.
video deep-learning pytorch sequence-to-sequence video-captioning s2vt msvd pytorch-implementation msrvtt marn video-captioning-models recnet
[AAAI 2023 Oral] VLTinT: Visual-Linguistic Transformer-in-Transformer for Coherent Video Paragraph Captioning
pytorch video-captioning transformer-architecture vision-language video-paragraph-captioning aaai2023
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