What goes around comes around: Cycle-Consistency-based Short-Term Motion Prediction for Anomaly Detection using Generative Adversarial Networks

  title={What goes around comes around: Cycle-Consistency-based Short-Term Motion Prediction for Anomaly Detection using Generative Adversarial Networks},
  author={Thomas Golda and Nils Murzyn and Chengchao Qu and Kristian Kroschel},
  journal={2019 16th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS)},
  • T. Golda, Nils Murzyn, +1 author K. Kroschel
  • Published 8 August 2019
  • Computer Science
  • 2019 16th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS)
Anomaly detection plays in many fields of research, along with the strongly related task of outlier detection, a very important role. Especially within the context of the automated analysis of video material recorded by surveillance cameras, abnormal situations can be of very different nature. For this purpose this work investigates Generative-Adversarial-Network-based methods (GAN) for anomaly detection related to surveillance applications. The focus is on the usage of static camera setups… Expand
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