Trending AI reposUpdated daily from GitHub
AI, coding & video AI repos ranked by star growth.
AI, coding & video AI repos ranked by star growth.
| # | Repo | Stars | 7d |
|---|---|---|---|
| 1 | OP open-mmlab/mmaction2 OpenMMLab's Next Generation Video Understanding Toolbox and Benchmark Video understanding | 5.2K | — |
| 2 | JI jinwchoi/awesome-action-recognition A curated list of action recognition and related area resources Video understanding | 4K | — |
| 3 | OP OpenGVLab/InternVideo [ECCV2024] Video Foundation Models & Data for Multimodal Understanding Video understanding | 2.4K | — |
| 4 | ZA zai-org/GLM-V GLM-4.6V/4.5V/4.1V-Thinking: Towards Versatile Multimodal Reasoning with Scalable Reinforcement Learning Video understanding | 2.4K | — |
| 5 | MI mit-han-lab/temporal-shift-module [ICCV 2019] TSM: Temporal Shift Module for Efficient Video Understanding Video understanding | 2.2K | — |
| 6 | HK HKUDS/VideoAgent [EMNLP2026] "VideoAgent: All-in-One Agentic Framework for Video Understanding and Editing, and Remaking" Video understanding | 2K | — |
| 7 | OP open-mmlab/mmaction An open-source toolbox for action understanding based on PyTorch Video understanding | 1.9K | — |
| 8 | MC MCG-NJU/VideoMAE [NeurIPS 2022 Spotlight] VideoMAE: Masked Autoencoders are Data-Efficient Learners for Self-Supervised Video Pre-Training Video understanding | 1.8K | — |
| 9 | 1.8K | — | |
| 10 | PA PaddlePaddle/PaddleVideo Awesome video understanding toolkits based on PaddlePaddle. It supports video data annotation tools, lightweight RGB and skeleton based action recognition model, practical applications for video tagging and sport action detection. Video understanding | 1.7K | — |
| 11 | YJ yjxiong/temporal-segment-networks Code & Models for Temporal Segment Networks (TSN) in ECCV 2016 Video understanding | 1.6K | — |
| 12 | BY bytedance/Lance A 3B-active-parameter native unified multimodal model for image and video understanding, generation, and editing. Video understanding | 1.4K | — |
| 13 | TH TheShadow29/awesome-grounding awesome grounding: A curated list of research papers in visual grounding Video understanding | 1.1K | — |
| 14 | YJ | 1.1K | — |
| 15 | NG | 1K | — |
| 16 | HH HHTseng/video-classification Tutorial for video classification/ action recognition using 3D CNN/ CNN+RNN on UCF101 Video understanding | 970 | — |
| 17 | PK PKU-YuanGroup/Chat-UniVi [CVPR 2024 Highlight🔥] Chat-UniVi: Unified Visual Representation Empowers Large Language Models with Image and Video Understanding Video understanding | 945 | — |
| 18 | FE felixchenfy/Realtime-Action-Recognition Real-time multi-person action recognition from OpenPose skeleton sequences, with tracking, feature extraction, model training, and inference pipelines for research and prototyping. Video understanding | 940 | — |
| 19 | JE jeffreyyihuang/two-stream-action-recognition Using two stream architecture to implement a classic action recognition method on UCF101 dataset Video understanding | 874 | — |
| 20 | HU HuaizhengZhang/Awsome-Deep-Learning-for-Video-Analysis Papers, code and datasets about deep learning and multi-modal learning for video analysis Video understanding | 847 | — |
| 21 | OP OpenGVLab/VideoMAEv2 [CVPR 2023] VideoMAE V2: Scaling Video Masked Autoencoders with Dual Masking Video understanding | 836 | — |
| 22 | OP OpenMOSS/MOSS-VL An open-weight 11B model series for long-form and real-time video understanding Video understanding | 832 | — |
| 23 | FI firework8/Awesome-Skeleton-based-Action-Recognition A curated paper list of awesome skeleton-based action recognition. Video understanding | 731 | — |
| 24 | DI | 719 | — |
| 25 | NI | 685 | — |
| 26 | YJ | 645 | — |
| 27 | VI Vision-CAIR/MiniGPT4-video Official code for Goldfish model for long video understanding and MiniGPT4-video for short video understanding Video understanding | 639 | — |
| 28 | BR bryanyzhu/two-stream-pytorch PyTorch implementation of two-stream networks for video action recognition Video understanding | 579 | — |
| 29 | HA | 579 | — |
| 30 | OX oxbshw/watch-skill Give AI agents eyes, ears, and verifiable results. Watch Skill turns video, audio and screen activity into searchable, timestamped evidence and proves work with deterministic contracts, not model opinion. DeepWatch is the agent workspace built on DeepSeek Harness. Python + npm, MCP, CLI, REST, Web. Video understanding | 577 | — |
| 31 | SA SAOS-3624/dsh-video-storyboard Scene-aware storyboard for DeepSeek Harness: 9-16 numbered cells with timestamps + transcript + an audio envelope, packed into ONE image (384 tokens). Two tools: video_storyboard and video_zoom. Video understanding | 535 | — |
| 32 | HE henghuiding/MeViS [ICCV 2023 & TPAMI 2025] MeViS: A Large-scale Benchmark for Video Segmentation with Motion Expressions Video understanding | 523 | — |
| 33 | ZE | 521 | — |
| 34 | AM | 501 | — |