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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 A machine learning-based video super resolution and frame interpolation framework. Est. Hack the Valley II, 2018. - k4yt3x/video2x Feb 25, 2025 · Wan: Open and Advanced Large-Scale Video Generative 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: Check the YouTube video’s resolution and the recommended speed needed to play the video. The table below shows the approximate speeds recommended to play each video resolution. LTX-Video is the first DiT-based video generation model that can generate high-quality videos in real-time. It can generate 30 FPS videos at 1216×704 resolution, faster than it takes to watch them. The model is trained on a large-scale dataset of diverse videos and can generate high-resolution videos with realistic and diverse content. The model supports image-to-video, keyframe-based Jan 21, 2025 · 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 Learn more about YouTube YouTube help videos Browse our video library for helpful tips, feature overviews, and step-by-step tutorials. YouTube Known Issues Get information on reported technical issues or scheduled maintenance. Apr 17, 2025 · Lets make video diffusion practical! Contribute to lllyasviel/FramePack development by creating an account on GitHub. 这是一个可以识别视频语音自动生成字幕SRT文件的开源 Windows-GUI 软件工具。. Contribute to
wxbool/video-srt-windows development by creating Contribute to kijai/ComfyUI-WanVideoWrapper development by creating an account on GitHub.
