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Adversarial Augmentation Training Makes Action Recognition Models More Robust to Realistic Video Distribution Shifts.

, , , , and . CoRR, (2024)

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Adversarial Augmentation Training Makes Action Recognition Models More Robust to Realistic Video Distribution Shifts., , , , and . CoRR, (2024)Synthetic Sample Selection for Generalized Zero-Shot Learning.. CVPR Workshops, page 58-67. IEEE, (2023)Using an ensemble color space model to tackle adversarial examples., and . CoRR, (2020)Fiducial Points Detection of a Face Using RBF-SVM and Adaboost Classification.. ACCV Workshops (1), volume 10116 of Lecture Notes in Computer Science, page 590-598. Springer, (2016)ColorNet: Investigating the importance of color spaces for image classification., and . CoRR, (2019)Age Estimation by LS-SVM Regression on Facial Images.. ISVC (2), volume 10073 of Lecture Notes in Computer Science, page 370-379. Springer, (2016)An advanced Diffie-Hellman approach to image steganography.. ANTS, page 1-4. IEEE, (2016)CLASTER: Clustering with Reinforcement Learning for Zero-Shot Action Recognition., , , and . ECCV (20), volume 13680 of Lecture Notes in Computer Science, page 187-203. Springer, (2022)Capturing Temporal Information in a Single Frame: Channel Sampling Strategies for Action Recognition., , , and . BMVC, page 355. BMVA Press, (2022)Learn2Augment: Learning to Composite Videos for Data Augmentation in Action Recognition., , , and . ECCV (31), volume 13691 of Lecture Notes in Computer Science, page 242-259. Springer, (2022)