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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 It can generate up to 50 fps videos at native 4k resolution with synchronized audio in one pass Learning united visual representation by alignment before projection if you like our project, please give us a star ⭐ on github for latest update

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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. Added a preliminary chapter, reclassifying video understanding tasks from the perspectives of granularity and language involvement, and enhanced the llm background section. Hack the valley ii, 2018

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. Wan2.1 offers these key features: