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  • DepthAnything Video-Depth-Anything - GitHub
    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 consistent depth accuracy
  • 【EMNLP 2024 】Video-LLaVA: Learning United Visual . . . - GitHub
    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 💡 I also have other video-language projects that may interest you Open-Sora Plan: Open-Source Large Video Generation Model
  • GitHub - MME-Benchmarks Video-MME: [CVPR 2025] Video-MME: The First . . .
    We introduce Video-MME, the first-ever full-spectrum, M ulti- M odal E valuation benchmark of MLLMs in Video analysis 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
  • Video-LLaMA: An Instruction-tuned Audio-Visual Language Model for Video . . .
    Video-LLaMA: An Instruction-tuned Audio-Visual Language Model for Video Understanding This is the repo for the Video-LLaMA project, which is working on empowering large language models with video and audio understanding capabilities
  • Video-R1: Reinforcing Video Reasoning in MLLMs - GitHub
    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
  • Troubleshoot YouTube video errors - Google Help
    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
  • VideoLLM-online: Online Video Large Language Model for Streaming Video
    Online Video Streaming: Unlike previous models that serve as offline mode (querying responding to a full video), our model supports online interaction within a video stream It can proactively update responses during a stream, such as recording activity changes or helping with the next steps in real time
  • GitHub - k4yt3x video2x: A machine learning-based video super . . .
    A machine learning-based video super resolution and frame interpolation framework Est Hack the Valley II, 2018 - k4yt3x video2x


















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