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achieves a new state-of-the-art accuracy of 35.8%, surping 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 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
Models In this repository, we present Wan2.1, a comprehensive and open suite of video foundation models that pushes the boundaries of video generation. Wan2.1 offers these key features: 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. A machine learning-based video super resolution and frame interpolation framework. Est. Hack the Valley II, 2018. -
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