DCTFormer: A Dual-Branch Transformer With Cloze Tests for Video Anomaly Detection

Video anomaly detection is of critical importance in safety-critical scenarios. The key challenge is to effectively capture the spatio-temporal features of videos and learn normal patterns from the training data. However, existing methods often fall short in modelling intra-channel and inter-channel...

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Bibliographic Details

Published in:	IEEE transactions on multimedia pp. 1 - 11
Main Authors:	Chen, Pengzhan, Du, Shengdong, Zhao, Xiaole, Hu, Jie, Li, Jingjing, Li, Tianrui
Format:	Journal Article
Language:	English
Published:	IEEE 2025
Subjects:	Anomaly detection Autoencoders conditional variational autoencoder Correlation Dynamics Feature extraction Optical flow Semantics Training transformer residual autoencoder Transformers unsupervised learning Video anomaly detection Videos
ISSN:	1520-9210, 1941-0077
Online Access:	Get full text
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