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Deep-Cascade: Cascading 3D Deep Neural Networks for Fast Anomaly Detection and Localization in Crowded Scenes.

, , , and . IEEE Trans. Image Process., 26 (4): 1992-2004 (2017)

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ATS: Adaptive Token Sampling For Efficient Vision Transformers., , , , , , and . CoRR, (2021)Taylor Swift: Taylor Driven Temporal Modeling for Swift Future Frame Prediction., , , , and . CoRR, (2021)SCT: Set Constrained Temporal Transformer for Set Supervised Action Segmentation., and . CVPR, page 498-507. Computer Vision Foundation / IEEE, (2020)AVID: Adversarial Visual Irregularity Detection., , , , , , and . ACCV (6), volume 11366 of Lecture Notes in Computer Science, page 488-505. Springer, (2018)Large Scale Holistic Video Understanding., , , , , , and . ECCV (5), volume 12350 of Lecture Notes in Computer Science, page 593-610. Springer, (2020)Fully Convolutional Neural Network for Fast Anomaly Detection in Crowded Scenes., , , and . CoRR, (2016)BERT on a Data Diet: Finding Important Examples by Gradient-Based Pruning., , , , , and . CoRR, (2022)3D CNNs With Adaptive Temporal Feature Resolutions., , , , , , and . CVPR, page 4731-4740. Computer Vision Foundation / IEEE, (2021)TaylorSwiftNet: Taylor Driven Temporal Modeling for Swift Future Frame Prediction., , , , , and . BMVC, page 389. BMVA Press, (2022)DecompX: Explaining Transformers Decisions by Propagating Token Decomposition., , , , and . ACL (1), page 2649-2664. Association for Computational Linguistics, (2023)