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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 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. Hack the valley ii, 2018 This highlights the necessity of explicit reasoning capability in solving video tasks, and confirms the. Wan2.1 offers these key features: Added a preliminary chapter, reclassifying video understanding tasks from the perspectives of granularity and language involvement, and enhanced the llm background section. Videollama 3 is a series of multimodal foundation models with frontier image and video understanding capacity

💡click here to show detailed performance on video benchmarks