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Countering Adversarial Images using Input Transformations., , , and . ICLR (Poster), OpenReview.net, (2018)Action2video: Generating Videos of Human 3D Actions., , , , , , and . Int. J. Comput. Vis., 130 (2): 285-315 (2022)Threats and Countermeasures in Machine Learning Applications.. Cornell University, USA, (2020)On Calibration of Modern Neural Networks, , , and . roceedings of the 34th International Conference on Machine Learning, 70, page 1321-1330. PMLR, (2017)A Preliminary Analysis of the Various Reaching Pattern Classifications., , , and . ICBBT, page 151-155. ACM, (2020)Generating Diverse and Natural 3D Human Motions from Text., , , , , , and . CVPR, page 5142-5151. IEEE, (2022)A New Defense Against Adversarial Images: Turning a Weakness into a Strength., , , , and . NeurIPS, page 1633-1644. (2019)Upper Extremity Kinematic Parameters: Reference Ranges Based on Kinect V2., , , , , , and . M2VIP, page 30-35. IEEE, (2021)Gradient-based Adversarial Attacks against Text Transformers., , , and . EMNLP (1), page 5747-5757. Association for Computational Linguistics, (2021)Promoting Saliency From Depth: Deep Unsupervised RGB-D Saliency Detection., , , , , and . ICLR, OpenReview.net, (2022)