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Video love sex. 1, a comprehensive and open suite of video foundation models that pushes the boundaries of video generation. 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 Video-LLaVA: Learning United Visual Representation by Alignment Before Projection If you like our project, please give us a star ⭐ on GitHub for latest update. A machine learning-based video super resolution and frame interpolation framework. 1 offers these key features: Video Overviews, including voices and visuals, are AI-generated and may contain inaccuracies or audio glitches. Compared with other diffusion-based models, it enjoys faster inference speed, fewer parameters, and higher consistent depth Feb 23, 2025 · Video-R1 significantly outperforms previous models across most benchmarks. It is designed to comprehensively assess the capabilities of MLLMs in processing video data, covering a wide range of visual domains, temporal durations, and data modalities. Open-Sora Plan: Open-Source Large Video Generation Model 知乎，中文互联网高质量的问答社区和创作者聚集的原创内容平台，于 2011 年 1 月正式上线，以「让人们更好的分享知识、经验和见解，找到自己的解答」为品牌使命。知乎凭借认真、专业、友善的社区氛围、独特的产品机制以及结构化和易获得的优质内容，聚集了中文互联网科技、商业、影视、时 We introduce Video-MME, the first-ever full-spectrum, M ulti- M odal E valuation benchmark of MLLMs in Video analysis. Jan 21, 2025 · ByteDance †Corresponding author 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. 0m ggqff ewx wysy9rq o8dlt cib1ctk ftm9u 3ir ykvbf tlfqao