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論文紹介:Learn2Augment: Learning to Composite Videos for Data Augmentation in Action Recognition

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論文紹介:Learn2Augment: Learning to Composite Videos for Data Augmentation in Action Recognition

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Shreyank N Gowda, Marcus Rohrbach, Frank Keller, Laura Sevilla-Lara, "Learn2Augment: Learning to Composite Videos for Data Augmentation in Action Recognition" ECCV2022

https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136910234.pdf
https://arxiv.org/abs/2206.04790

Shreyank N Gowda, Marcus Rohrbach, Frank Keller, Laura Sevilla-Lara, "Learn2Augment: Learning to Composite Videos for Data Augmentation in Action Recognition" ECCV2022

https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136910234.pdf
https://arxiv.org/abs/2206.04790

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論文紹介:Learn2Augment: Learning to Composite Videos for Data Augmentation in Action Recognition

  1. 1. Learn2Augment: Learning to Composite Videos for Data Augmentation in Action Recognition Shreyank N Gowda, Marcus Rohrbach, Frank Keller, and Laura Sevilla-Lara , ECCV2022 2022/11/25
  2. 2. nLearn2Augment • •
  3. 3. nData Augmentation • ActorCut [Zou+, arXiv2021] VideoMix [Yun+, arXiv2020] • • [Zhang+, arXiv2019] • GAN • self-paced selection nSemi-supervised Video Action Recognition • • VideoSSL [Jing+, WACV2021] • • Temporal Contrastive Learning (TCL) [Singh+, CVPR2021] • 2
  4. 4. nSample selection • [Huang+, CVPR2018] • • SMART [Gowda+, arXiv2020] • • SCSampler [Korbar+, ICCV2019] • • • RL [Yoon+, PMLR2020] • •
  5. 5. Learn2Augment 1. Semantic Match • 2. Selector 1. Selector 𝜔 2. Video Composite 1. • • 2. 3. Classifier & Selector Reword 3.
  6. 6. Semantic Matching n[Choi+, NIPS2019] • • nSen2vec [Pagliardini+, arXiv2018] • • 𝑐! 𝑐" 𝑉!, 𝑉"
  7. 7. Selector nSelector Architecture • 3D ResNet-18 [He+, arXiv2016] + MLP • n • 3D ResNet-18 validation loss n •
  8. 8. Training Selector nSelector • RL 1. • 𝐷#$%: validation set ℒ&%': • 𝑓(: 𝑉): 𝑦): • 𝛿: • 𝑆:
  9. 9. Training Selector 2. REINFORCE [Williams+, Machine learning1992] • • 𝐷*: • 𝐷+:
  10. 10. Video Compositing 1. • MaskRCNN [He+, ICCV2017] • MaskRCNN COCO [Lin+, ECCV2014] • 2. • • [Liu+, ECCV2018] 3.
  11. 11. Training Classifier n • , 𝑦 • 𝛾 = ∑ *! ,-. 𝛼 = 4 • 𝑦/ 𝑦0
  12. 12. n • • • • Few-shot • n+k k • Novel-class • 1~5 • Seen-class • • • Standard split [Zhang+, arXiv2020] • Truze split [Gowda+, arXiv2021] • • • • • Sports1M [Karpathy+, CVPR2014] n • HMDB51 [Jhuang+, ICCV2011] • UCF101 [Soomro+, arXiv, 2012] • Kinetics-400 [Kay+, arXiv2017] • Kinetics-100
  13. 13. 1 n • 13.4% •
  14. 14. 2 n • Top-1 accuracy • 5~50% • L2A Pre-training • Kinetics-400 Selector
  15. 15. 3 nFew-shot • Top-1 accuracy • S: Standard split, T: Truze split
  16. 16. 4 n • L2A
  17. 17. nLearn2Augment • • n • • 8.6% • Few-shot • 3.7% • • 17.4%

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