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comprehensive and open suite of video foundation models that pushes the boundaries of video generation. Wan2.1 offers these key features: 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 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 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. A machine learning-based video super resolution and frame interpolation framework. Est. Hack the Valley II, 2018. - k4yt3x/video2x Mar 26, 2025 · Qwen2.5-Omni is an end-to-end multimodal model by Qwen team at Alibaba Cloud, capable of understanding text, audio, vision, video, and performing real-time speech generation. CVPR 2025 ่ฎบๆ–‡ๅ’Œๅผ€ๆบ้กน็›ฎๅˆ้›†. Contribute to amusi/CVPR2025-Papers-with-Code development by creating an account on GitHub. LTX-Video Support for ComfyUI. Contribute to Lightricks/ComfyUI-LTXVideo development by creating an account on GitHub. Jan 13, 2025 · HunyuanVideo introduces the Transformer design and employs a Full Attention mechanism for unified image and video generation. Specifically, we use a "Dual-stream to Single-stream" hybrid model design for video generation. In the dual-stream phase, video and text tokens are processed

independently through multiple Transformer blocks, enabling each modality to learn its own appropriate ๐Ÿ”ฅ๐Ÿ”ฅ๐Ÿ”ฅLatest Papers, Codes and Datasets on Vid-LLMs. Contribute to yunlong10/Awesome-LLMs-for-Video-Understanding development by creating an account on GitHub.

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