# image classification by deep learning
@inproceedings{a,
  author    = {Mikołajczyk, Agnieszka and Grochowski, Michał},
  booktitle = {2018 International Interdisciplinary PhD Workshop (IIPhDW)},
  title     = {Data augmentation for improving deep learning in image classification problem},
  year      = {2018},
  volume    = {},
  number    = {},
  pages     = {117-122},
  doi       = {10.1109/IIPHDW.2018.8388338}
}

# R(2+1)D
@inproceedings{2,
  author    = {Du Tran and
               Heng Wang and
               Lorenzo Torresani and
               Jamie Ray and
               Yann LeCun and
               Manohar Paluri},
  title     = {A Closer Look at Spatiotemporal Convolutions for Action Recognition},
  booktitle = {2018 {IEEE} Conference on Computer Vision and Pattern Recognition,
               {CVPR} 2018, Salt Lake City, UT, USA, June 18-22, 2018},
  pages     = {6450--6459},
  publisher = {{IEEE} Computer Society},
  year      = {2018},
  url       = {http://openaccess.thecvf.com/content\_cvpr\_2018/html/Tran\_A\_Closer\_Look\_CVPR\_2018\_paper.html},
  doi       = {10.1109/CVPR.2018.00675},
  timestamp = {Wed, 16 Oct 2019 14:14:50 +0200},
  biburl    = {https://dblp.org/rec/conf/cvpr/TranWTRLP18.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

# R3D
@inproceedings{3,
  author    = {Kensho Hara and
               Hirokatsu Kataoka and
               Yutaka Satoh},
  title     = {Can Spatiotemporal 3D CNNs Retrace the History of 2D CNNs and ImageNet?},
  booktitle = {2018 {IEEE} Conference on Computer Vision and Pattern Recognition,
               {CVPR} 2018, Salt Lake City, UT, USA, June 18-22, 2018},
  pages     = {6546--6555},
  publisher = {{IEEE} Computer Society},
  year      = {2018},
  url       = {http://openaccess.thecvf.com/content\_cvpr\_2018/html/Hara\_Can\_Spatiotemporal\_3D\_CVPR\_2018\_paper.html},
  doi       = {10.1109/CVPR.2018.00685},
  timestamp = {Wed, 16 Oct 2019 14:14:50 +0200},
  biburl    = {https://dblp.org/rec/conf/cvpr/HaraKS18.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

# adversarial examples
@inproceedings{4,
  author    = {Shehzeen Hussain and
               Paarth Neekhara and
               Malhar Jere and
               Farinaz Koushanfar and
               Julian J. McAuley},
  title     = {Adversarial Deepfakes: Evaluating Vulnerability of Deepfake Detectors
               to Adversarial Examples},
  booktitle = {{IEEE} Winter Conference on Applications of Computer Vision, {WACV}
               2021, Waikoloa, HI, USA, January 3-8, 2021},
  pages     = {3347--3356},
  publisher = {{IEEE}},
  year      = {2021},
  url       = {https://doi.org/10.1109/WACV48630.2021.00339},
  doi       = {10.1109/WACV48630.2021.00339},
  timestamp = {Fri, 18 Jun 2021 12:30:06 +0200},
  biburl    = {https://dblp.org/rec/conf/wacv/HussainNJKM21.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

# adversarial examples FGSM
@inproceedings{5,
  author    = {Ian J. Goodfellow and
               Jonathon Shlens and
               Christian Szegedy},
  editor    = {Yoshua Bengio and
               Yann LeCun},
  title     = {Explaining and Harnessing Adversarial Examples},
  booktitle = {3rd International Conference on Learning Representations, {ICLR} 2015,
               San Diego, CA, USA, May 7-9, 2015, Conference Track Proceedings},
  year      = {2015},
  url       = {http://arxiv.org/abs/1412.6572},
  timestamp = {Thu, 25 Jul 2019 14:25:38 +0200},
  biburl    = {https://dblp.org/rec/journals/corr/GoodfellowSS14.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

# sparse attack
@inproceedings{6,
  author    = {Xingxing Wei and
               Jun Zhu and
               Sha Yuan and
               Hang Su},
  title     = {Sparse Adversarial Perturbations for Videos},
  booktitle = {The Thirty-Third {AAAI} Conference on Artificial Intelligence, {AAAI}
               2019, The Thirty-First Innovative Applications of Artificial Intelligence
               Conference, {IAAI} 2019, The Ninth {AAAI} Symposium on Educational
               Advances in Artificial Intelligence, {EAAI} 2019, Honolulu, Hawaii,
               USA, January 27 - February 1, 2019},
  pages     = {8973--8980},
  publisher = {{AAAI} Press},
  year      = {2019},
  url       = {https://doi.org/10.1609/aaai.v33i01.33018973},
  doi       = {10.1609/aaai.v33i01.33018973},
  timestamp = {Tue, 02 Feb 2021 08:00:59 +0100},
  biburl    = {https://dblp.org/rec/conf/aaai/WeiZYS19.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

# appending attack
@inproceedings{7,
  author    = {Zhikai Chen and
               Lingxi Xie and
               Shanmin Pang and
               Yong He and
               Qi Tian},
  title     = {Appending Adversarial Frames for Universal Video Attack},
  booktitle = {{IEEE} Winter Conference on Applications of Computer Vision, {WACV}
               2021, Waikoloa, HI, USA, January 3-8, 2021},
  pages     = {3198--3207},
  publisher = {{IEEE}},
  year      = {2021},
  url       = {https://doi.org/10.1109/WACV48630.2021.00324},
  doi       = {10.1109/WACV48630.2021.00324},
  timestamp = {Fri, 18 Jun 2021 12:30:06 +0200},
  biburl    = {https://dblp.org/rec/conf/wacv/ChenXPH021.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

# 人体骨骼识别对抗样本
@inproceedings{8,
  author    = {He Wang and
               Feixiang He and
               Zhexi Peng and
               Tianjia Shao and
               Yong{-}Liang Yang and
               Kun Zhou and
               David Hogg},
  title     = {Understanding the Robustness of Skeleton-Based Action Recognition
               Under Adversarial Attack},
  booktitle = {{IEEE} Conference on Computer Vision and Pattern Recognition, {CVPR}
               2021, virtual, June 19-25, 2021},
  pages     = {14656--14665},
  publisher = {Computer Vision Foundation / {IEEE}},
  year      = {2021},
  url       = {https://openaccess.thecvf.com/content/CVPR2021/html/Wang\_Understanding\_the\_Robustness\_of\_Skeleton-Based\_Action\_Recognition\_Under\_Adversarial\_Attack\_CVPR\_2021\_paper.html},
  timestamp = {Mon, 30 Aug 2021 17:00:27 +0200},
  biburl    = {https://dblp.org/rec/conf/cvpr/0002HPSY0H21.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

# UCF101数据集
@article{9,
  author        = {Khurram Soomro and
               Amir Roshan Zamir and
               Mubarak Shah},
  title         = {{UCF101:} {A} Dataset of 101 Human Actions Classes From Videos in
               The Wild},
  journal       = {CoRR},
  volume        = {abs/1212.0402},
  year          = {2012},
  url           = {http://arxiv.org/abs/1212.0402},
  archiveprefix = {arXiv},
  eprint        = {1212.0402},
  timestamp     = {Mon, 13 Aug 2018 16:47:45 +0200},
  biburl        = {https://dblp.org/rec/journals/corr/abs-1212-0402.bib},
  bibsource     = {dblp computer science bibliography, https://dblp.org}
}

# i3d
@inproceedings{10,
  author    = {Jo{\~{a}}o Carreira and
               Andrew Zisserman},
  title     = {Quo Vadis, Action Recognition? {A} New Model and the Kinetics Dataset},
  booktitle = {2017 {IEEE} Conference on Computer Vision and Pattern Recognition,
               {CVPR} 2017, Honolulu, HI, USA, July 21-26, 2017},
  pages     = {4724--4733},
  publisher = {{IEEE} Computer Society},
  year      = {2017},
  url       = {https://doi.org/10.1109/CVPR.2017.502},
  doi       = {10.1109/CVPR.2017.502},
  timestamp = {Wed, 16 Oct 2019 14:14:50 +0200},
  biburl    = {https://dblp.org/rec/conf/cvpr/CarreiraZ17.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

# mmaction2
@misc{11,
  title        = {OpenMMLab's Next Generation Video Understanding Toolbox and Benchmark},
  author       = {MMAction2 Contributors},
  howpublished = {\url{https://github.com/open-mmlab/mmaction2}},
  year         = {2020}
}

# pgd
@inproceedings{12,
  author    = {Aleksander Madry and
               Aleksandar Makelov and
               Ludwig Schmidt and
               Dimitris Tsipras and
               Adrian Vladu},
  title     = {Towards Deep Learning Models Resistant to Adversarial Attacks},
  booktitle = {6th International Conference on Learning Representations, {ICLR} 2018,
               Vancouver, BC, Canada, April 30 - May 3, 2018, Conference Track Proceedings},
  publisher = {OpenReview.net},
  year      = {2018},
  url       = {https://openreview.net/forum?id=rJzIBfZAb},
  timestamp = {Thu, 25 Jul 2019 14:25:44 +0200},
  biburl    = {https://dblp.org/rec/conf/iclr/MadryMSTV18.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

# cw attack
@inproceedings{13,
  author    = {Nicholas Carlini and
               David A. Wagner},
  title     = {Towards Evaluating the Robustness of Neural Networks},
  booktitle = {2017 {IEEE} Symposium on Security and Privacy, {SP} 2017, San Jose,
               CA, USA, May 22-26, 2017},
  pages     = {39--57},
  publisher = {{IEEE} Computer Society},
  year      = {2017},
  url       = {https://doi.org/10.1109/SP.2017.49},
  doi       = {10.1109/SP.2017.49},
  timestamp = {Wed, 16 Oct 2019 14:14:51 +0200},
  biburl    = {https://dblp.org/rec/conf/sp/Carlini017.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}