Publisher
Springer Nature Switzerland
Reference53 articles.
1. Anand, A.P., Gokul, H., Srinivasan, H., Vijay, P., Vijayaraghavan, V.: Adversarial patch defense for optical flow networks in video action recognition. In: Proceedings of the IEEE International Conference on Machine Learning and Applications (ICMLA), pp. 1289–1296 (2020)
2. Baker, S., Scharstein, D., Lewis, J.P., Roth, S., Black, M.J., Szeliski, R.: A database and evaluation methodology for optical flow. Int. J. Comput. Vis. 92(1), 1–31 (2011)
3. Barron, J.L., Fleet, D.J., Beauchemin, S.S.: Performance of optical flow techniques. Int. J. Comput. Vis. 12, 43–77 (1994)
4. Black, M.J., Anandan, P.: A framework for the robust estimation of optical flow. In: Proceedings of the IEEE International Conference on Computer Vision (ICCV), pp. 231–236 (1993)
5. Brown, T.B., Mané, D., Roy, A., Abadi, M., Gilmer, J.: Adversarial patch. In: arXiv preprint. arXiv:1712 (2018)
Cited by
6 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Physical Attack for Stereo Matching;Proceedings of the International Conference on Computer Vision and Deep Learning;2024-01-19
2. Detection Defenses: An Empty Promise against Adversarial Patch Attacks on Optical Flow;2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV);2024-01-03
3. The Robustness of Machine Learning Models Using MLSecOps: A Case Study On Delivery Service Forecasting;2023 14th International Conference on Information & Communication Technology and System (ICTS);2023-10-04
4. Distracting Downpour: Adversarial Weather Attacks for Motion Estimation;2023 IEEE/CVF International Conference on Computer Vision (ICCV);2023-10-01
5. Spring: A High-Resolution High-Detail Dataset and Benchmark for Scene Flow, Optical Flow and Stereo;2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR);2023-06