| Revisiting batch normalization for improving corruption robustness P Benz, C Zhang, A Karjauv, IS Kweon Proceedings of the IEEE/CVF winter conference on applications of computer …, 2021 | 46 | 2021 |
| A survey on universal adversarial attack C Zhang, P Benz, C Lin, A Karjauv, J Wu, IS Kweon arXiv preprint arXiv:2103.01498, 2021 | 45 | 2021 |
| Udh: Universal deep hiding for steganography, watermarking, and light field messaging C Zhang, P Benz, A Karjauv, G Sun, IS Kweon Advances in Neural Information Processing Systems 33, 10223-10234, 2020 | 44 | 2020 |
| Adversarial robustness comparison of vision transformer and mlp-mixer to cnns P Benz, S Ham, C Zhang, A Karjauv, IS Kweon arXiv preprint arXiv:2110.02797, 2021 | 26 | 2021 |
| Universal adversarial perturbations through the lens of deep steganography: Towards a fourier perspective C Zhang, P Benz, A Karjauv, IS Kweon Proceedings of the AAAI Conference on Artificial Intelligence 35 (4), 3296-3304, 2021 | 25 | 2021 |
| Robustness may be at odds with fairness: An empirical study on class-wise accuracy P Benz, C Zhang, A Karjauv, IS Kweon NeurIPS 2020 Workshop on Pre-registration in Machine Learning, 325-342, 2021 | 16 | 2021 |
| Universal adversarial training with class-wise perturbations P Benz, C Zhang, A Karjauv, IS Kweon 2021 IEEE International Conference on Multimedia and Expo (ICME), 1-6, 2021 | 16 | 2021 |
| Data-free universal adversarial perturbation and black-box attack C Zhang, P Benz, A Karjauv, IS Kweon Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 13 | 2021 |
| Towards robust deep hiding under non-differentiable distortions for practical blind watermarking C Zhang, A Karjauv, P Benz, IS Kweon Proceedings of the 29th ACM international conference on multimedia, 5158-5166, 2021 | 11 | 2021 |
| Towards robust data hiding against (jpeg) compression: A pseudo-differentiable deep learning approach C Zhang, A Karjauv, P Benz, IS Kweon arXiv preprint arXiv:2101.00973, 2020 | 8 | 2020 |
| Robustness comparison of vision transformer and MLP-Mixer to CNNs P Benz, C Zhang, S Ham, A Karjauv, IS Kweon CVPR 2021 Workshop on Adversarial Machine Learning in Real-World Computer …, 2021 | 7 | 2021 |
| Investigating top-k white-box and transferable black-box attack C Zhang, P Benz, A Karjauv, JW Cho, K Zhang, IS Kweon Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 4 | 2022 |
| Backpropagating smoothly improves transferability of adversarial examples C Zhang, P Benz, G Cho, A Karjauv, S Ham, CH Youn, IS Kweon CVPR 2021 Workshop Workshop on Adversarial Machine Learning in Real-World …, 2021 | 3 | 2021 |
| Trade-off between accuracy, robustness, and fairness of deep classifiers P Benz, C Zhang, S Ham, A Karjauv, G Cho, IS Kweon | 2 | 2021 |
| Motionsnap: A Motion Sensor-Based Approach for Automatic Capture and Editing of Photos and Videos on Smartphones A Karjauv, S Bakhtiyarov, C Zhang, JC Bazin, IS Kweon 2021 IEEE International Conference on Multimedia and Expo (ICME), 1-6, 2021 | | 2021 |
| Is FGSM Optimal or Necessary for L∞ Adversarial Attack? C Zhang, A Karjauv, P Benz, S Ham, G Cho, CH Youn, IS Kweon Workshop on Adversarial Machine Learning in Real-World Computer Vision …, 2021 | | 2021 |
| Towards robust deep hiding under non-differentiable distortions for practical blind watermarking A Karjauv 한국과학기술원, 2021 | | 2021 |
| Data-free Universal Adversarial Perturbation and Black-box Attack Supplementary Material C Zhang, P Benz, A Karjauv, IS Kweon | | |
| MapIt: Collaborative student summary with concept maps A Yerembessov, A Karjauv, A Poppele, N Kim | | |
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