Toward Video Anomaly Retrieval From Video Anomaly Detection: New Benchmarks and Model-Reference-Cited by-同舟云学术

Toward Video Anomaly Retrieval From Video Anomaly Detection: New Benchmarks and Model

Published:2024 Issue: Volume:33 Page:2213-2225
ISSN:1057-7149
Container-title:IEEE Transactions on Image Processing
language:
Short-container-title:IEEE Trans. on Image Process.

Author:

Wu Peng¹^ORCID,Liu Jing²^ORCID,He Xiangteng³^ORCID,Peng Yuxin³^ORCID,Wang Peng¹^ORCID,Zhang Yanning¹^ORCID

Affiliation:

1. National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology, School of Computer Science, Northwestern Polytechnical University, Xi’an, China

2. Guangzhou Institute of Technology, Xidian University, Guangzhou, China

3. Wangxuan Institute of Computer Technology, Peking University, Beijing, China

Funder

National Natural Science Foundation of China

China Postdoctoral Science Foundation

Fundamental Research Funds for the Central Universities

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/83/10346232/10471334.pdf?arnumber=10471334

Reference90 articles.

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

2. Future Frame Prediction for Anomaly Detection - A New Baseline

3. A Deep One-Class Neural Network for Anomalous Event Detection in Complex Scenes

4. Learning Memory-Guided Normality for Anomaly Detection

5. Anomaly Detection in Video via Self-Supervised and Multi-Task Learning

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