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Exploiting Feature and Class Relationships in Video Categorization with Regularized Deep Neural Networks., , , , and . IEEE Trans. Pattern Anal. Mach. Intell., 40 (2): 352-364 (2018)Emotion in Context: Deep Semantic Feature Fusion for Video Emotion Recognition., , and . ACM Multimedia, page 127-131. ACM, (2016)VITON: An Image-Based Virtual Try-On Network., , , , and . CVPR, page 7543-7552. IEEE Computer Society, (2018)ACE: Adapting to Changing Environments for Semantic Segmentation., , , , and . CoRR, (2019)M2KD: Multi-model and Multi-level Knowledge Distillation for Incremental Learning., , , , , and . CoRR, (2019)Multi-Stream Multi-Class Fusion of Deep Networks for Video Classification., , , , and . ACM Multimedia, page 791-800. ACM, (2016)Fudan-NJUST at MediaEval 2014: Violent Scenes Detection Using Deep Neural Networks., , , , and . MediaEval, volume 1263 of CEUR Workshop Proceedings, CEUR-WS.org, (2014)Learning Semantic Feature Map for Visual Content Recognition., , , and . ACM Multimedia, page 1291-1299. ACM, (2017)Making an Invisibility Cloak: Real World Adversarial Attacks on Object Detectors., , , and . CoRR, (2019)SAM: Modeling Scene, Object and Action With Semantics Attention Modules for Video Recognition., , and . IEEE Trans. Multim., (2022)