Changed video processing section (Unit 7 - CNN Based Video Model) #356
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Hello @cjfghk5697 😄 I think you haven't modified _toctree.yml file yet. |
johko
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Oct 26, 2024
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| In this paper, the authors applied the ResNet architecture to the 3D CNNs. This approach introduces deeper models for 3D CNNs and achieves higher accuracy. | ||
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| Experiments showed that the 3D ResNets (especially deeper ones like the ResNet-34) outperform models like the C3D, particularly on larger datasets. Pretrained models like Sports-1M C3D can help mitigate overfitting on smaller datasets. Overall, 3D ResNets effectively leverage deeper architectures to capture complex spatiotemporal patterns in the video data. |
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Here you mention C3D as if it is already known, maybe shortly introduce it or give a link to the paper?
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Thank you for reviewing it! I’ve added C3D research paper's link.
Co-authored-by: Johannes Kolbe <[email protected]>
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Changed
chapters/en/unit7/video-processing/overview-of-previous-sota-models.mdxtochapters/en/unit7/video-processing/cnn-based-video-model.mdxat video processing section. This document provides an overview of various CNN video architectures which integrate different kinds of modalities into a unified representation space.Part of #348
Who can review? (Initial)
@jungnerd @cjfghk5697 @mreraser and anyone who wants to review!