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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 About 🎬 卡卡字幕助手 | VideoCaptioner - 基于 LLM 的智能字幕助手 - 视频字幕生成、断句、校正、字幕翻译全流程处理! - A powered tool for easy and efficient video subtitling. Contribute to kijai/ComfyUI-WanVideoWrapper development by creating an account on GitHub. 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. LTX-Video Support for ComfyUI. Contribute to Lightricks/ComfyUI-LTXVideo development by creating an account on GitHub.