Online video streaming unlike previous models that serve as offline mode queryingresponding to a full video, our model supports online interaction within a video stream.

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1. Compared with other diffusionbased models, it enjoys faster inference speed, fewer parameters, and higher consistent depth accuracy.
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5. Compared with other diffusionbased models, it enjoys faster inference speed, fewer parameters, and higher consistent depth accuracy.
6. Notebooklm may take a while to generate the video overview sometimes, more than 30 minutes.
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10. Video overviews, including voices and visuals, are aigenerated and may contain inaccuracies or audio glitches.
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26. Compared with other diffusionbased models, it enjoys faster inference speed, fewer parameters, and higher consistent depth accuracy.
27. Notebooklm may take a while to generate the video overview sometimes, more than 30 minutes.
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30. Online video streaming unlike previous models that serve as offline mode queryingresponding to a full video, our model supports online interaction within a video stream.
31. 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.
32. It brings together all the techniques allowing the constitution or restitution of electrical signal representing moving images.
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35. Compared with other diffusionbased models, it enjoys faster inference speed, fewer parameters, and higher consistent depth accuracy.
36. Notebooklm may take a while to generate the video overview sometimes, more than 30 minutes.
37. It brings together all the techniques allowing the constitution or restitution of electrical signal representing moving images.
38. 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.
39. Compared with other diffusionbased models, it enjoys faster inference speed, fewer parameters, and higher consistent depth accuracy.
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46. We introduce videomme, the firstever fullspectrum, m ulti m odal e valuation benchmark of mllms in video analysis.
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48. Notebooklm may take a while to generate the video overview sometimes, more than 30 minutes.
49. Compared with other diffusionbased models, it enjoys faster inference speed, fewer parameters, and higher consistent depth accuracy.