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ๅพฎไฟก่ง้ขๅท็่ง้ขไธ่ฝฝไธ็ดๆฏไธช้พ้ข๏ผๆฌ่ฝฏไปถๅฏ่ฝปๆพ่งฃๅณใ ็น็น๏ผ็้ขๆด็พๅ๏ผไฝ็งฏๅฐๅทง๏ผๅชๆ5MB๏ผ่ไธๆฏๅฎๅ จๅ ่ดนใๆ ้ๅฎ่ฃ ๏ผๅฏๅ ่ดนไธ่ฝฝ่ง้ขๅท่ง้ข๏ผไธ้ซๆธ ๅ็ป่ดจ้๏ผๆฒกๆไปปไฝ ๆฐดๅฐใ … 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: Jan 21, 2025 · VideoLLaMA 3 is a series of multimodal foundation models with frontier image and video understanding capacity. ๐กClick here to show detailed performance on video benchmarks VisoMaster is a powerful yet easy-to-use tool for face swapping and editing in images and videos. It utilizes AI to produce natural-looking results with minimal effort, making it ideal for both casual users and professionals. 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. About ๐ฌ ๅกๅกๅญๅนๅฉๆ | VideoCaptioner - ๅบไบ LLM ็ๆบ่ฝๅญๅนๅฉๆ -
่ง้ขๅญๅน็ๆใๆญๅฅใๆ กๆญฃใๅญๅน็ฟป่ฏๅ จๆต็จๅค็๏ผ - A powered tool for easy and efficient video subtitling. Feb 25, 2025 · Contribute to kijai/ComfyUI-WanVideoWrapper development by creating an account on GitHub. A machine learning-based video super resolution and frame interpolation framework. Est. Hack the Valley II, 2018. - k4yt3x/video2x VACE is an all-in-one model designed for video creation and editing. It encompasses various tasks, including reference-to-video generation (R2V), video-to-video editing (V2V), and masked video-to-video editing (MV2V), allowing users to compose these tasks freely. This functionality enables users to explore diverse possibilities and streamlines their workflows effectively, offering a range of
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