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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: Jul 28, 2025 · Wan: Open and Advanced Large-Scale Video Generative Models We are excited to introduce Wan2.2, a major upgrade to our foundational video models. With Wan2.2, we have focused on incorporating the following innovations: đ Effective MoE Architecture: Wan2.2 introduces a Mixture-of-Experts (MoE) architecture into video diffusion models. Contribute to kijai/ComfyUI-WanVideoWrapper development by creating an account on GitHub. 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 Feb 23, 2025 · 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 A machine learning-based video super resolution and frame interpolation framework. Est. Hack the Valley II, 2018. - k4yt3x/video2x About đŹ ĺĄĺĄĺĺšĺŠć | VideoCaptioner - ĺşäş LLM çćşč˝ĺĺšĺŠć - č§é˘ĺĺšçćăćĺĽăć ĄćŁăĺĺšçżťčŻĺ ¨ćľç¨ĺ¤çďź - A powered tool for easy and efficient video subtitling. 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. Introduced a novel taxonomy for Vid-LLMs based on video representation and LLM functionality. Added a Preliminary chapter, reclassifying video understanding tasks from the perspectives of granularity and language involvement, and enhanced the LLM Background section. A fast AI Video Generator for the GPU Poor. Supports Wan 2.1/2.2, Hunyuan Video, LTX Video and Flux. - deepbeepmeep/Wan2GP
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