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- DepthAnything Video-Depth-Anything - GitHub
This work presents Video Depth Anything based on Depth Anything V2, which can be applied to arbitrarily long videos without compromising quality, consistency, or generalization ability Compared with other diffusion-based models, it enjoys faster inference speed, fewer parameters, and higher consistent depth accuracy
- 【EMNLP 2024 】Video-LLaVA: Learning United Visual . . . - GitHub
Video-LLaVA: Learning United Visual Representation by Alignment Before Projection If you like our project, please give us a star ⭐ on GitHub for latest update 💡 I also have other video-language projects that may interest you Open-Sora Plan: Open-Source Large Video Generation Model
- Video-LLaMA: An Instruction-tuned Audio-Visual Language Model for Video . . .
Video-LLaMA: An Instruction-tuned Audio-Visual Language Model for Video Understanding This is the repo for the Video-LLaMA project, which is working on empowering large language models with video and audio understanding capabilities
- Video-R1: Reinforcing Video Reasoning in MLLMs - GitHub
Video-R1 significantly outperforms previous models across most benchmarks Notably, on VSI-Bench, which focuses on spatial reasoning in videos, Video-R1-7B achieves a new state-of-the-art accuracy of 35 8%, surpassing GPT-4o, a proprietary model, while using only 32 frames and 7B parameters This highlights the necessity of explicit reasoning capability in solving video tasks, and confirms the
- Generate Video Overviews in NotebookLM - Google Help
Video Overviews, including voices and visuals, are AI-generated and may contain inaccuracies or audio glitches NotebookLM may take a while to generate the Video Overview, feel free to come back to your notebook later
- GitHub - jh-yi Video-Panda: Video-Panda: Parameter-efficient Alignment . . .
Video-Panda is an encoder-free video conversation model that directly processes video inputs through a novel spatio-temporal alignment block (STAB) It eliminates the need for heavyweight pretrained encoders and requires less than 50M parameters
- VideoLLM-online: Online Video Large Language Model for Streaming Video
Online Video Streaming: Unlike previous models that serve as offline mode (querying responding to a full video), our model supports online interaction within a video stream It can proactively update responses during a stream, such as recording activity changes or helping with the next steps in real time
- GitHub - Lightricks LTX-Video: Official repository for LTX-Video
LTX-Video is the first DiT-based video generation model that contains all core capabilities of modern video generation in one model: synchronized audio and video, high fidelity, multiple performance modes, production-ready outputs, API access, and open access It can generate up to 50 FPS videos at native 4K resolution with synchronized audio in one pass The model is trained on a large-scale
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