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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
PKU-YuanGroup Video-LLaVA - GitHub 😮 Highlights Video-LLaVA exhibits remarkable interactive capabilities between images and videos, despite the absence of image-video pairs in the dataset
Video-R1: Reinforcing Video Reasoning in MLLMs - GitHub Inspired by DeepSeek-R1's success in eliciting reasoning abilities through rule-based RL, we introduce Video-R1 as the first work to systematically explore the R1 paradigm for eliciting video reasoning within MLLMs
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
Download the Google Meet app - Computer - Google Meet Help Accessories and hardware kits for Meet Set up Meet to help your team work remotely Accessibility in Google Meet Get the new Meet app in the play store or app store Google Meet is your one app for video calling and meetings across all devices Use video calling features like fun filters and effects or schedule time to connect when everyone can join
YouTube Shorts - Google Help Fix a problem Watch videos Manage your account settings Supervised experiences on YouTube YouTube Premium Create grow your channel Monetize with the YouTube Partner Program Policy, safety, copyright
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-3D LLM: Learning Position-Aware Video Representation for 3D Scene . . . We propose a novel generalist model, i e , Video-3D LLM, for 3D scene understanding By treating 3D scenes as dynamic videos and incorporating 3D position encoding into these representations, our Video-3D LLM aligns video representations with real-world spatial contexts more accurately
video · GitHub Topics · GitHub Video is an electronic medium for the recording, copying, playback, broadcasting, and display of moving visual media It brings together all the techniques allowing the constitution or restitution of electrical signal representing moving images