Understanding the Challenges and Opportunities of Pose-based Anomaly Detection-Reference-Cited by-同舟云学术

Understanding the Challenges and Opportunities of Pose-based Anomaly Detection

Published:2023-09-21 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 8th international Workshop on Sensor-Based Activity Recognition and Artificial Intelligence
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Author:

Alinezhad Noghre Ghazal¹^ORCID,Danesh Pazho Armin¹^ORCID,Katariya Vinit¹^ORCID,Tabkhi Hamed¹^ORCID

Affiliation:

1. University of North Carolina at Charlotte, USA

Funder

National Science Foundation

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3615834.3615844

Reference36 articles.

1. UBnormal: New Benchmark for Supervised Open-Set Video Anomaly Detection

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3. Automated Real-time Anomaly Detection in Human Trajectories using Sequence to Sequence Networks

4. Rethinking Video Anomaly Detection - A Continual Learning Approach

5. Hao-Shu Fang , Jiefeng Li , Hongyang Tang , Chao Xu , Haoyi Zhu , Yuliang Xiu , Yong-Lu Li , and Cewu Lu. 2022. AlphaPose: Whole-Body Regional Multi-Person Pose Estimation and Tracking in Real-Time . IEEE Transactions on Pattern Analysis and Machine Intelligence ( 2022 ). Hao-Shu Fang, Jiefeng Li, Hongyang Tang, Chao Xu, Haoyi Zhu, Yuliang Xiu, Yong-Lu Li, and Cewu Lu. 2022. AlphaPose: Whole-Body Regional Multi-Person Pose Estimation and Tracking in Real-Time. IEEE Transactions on Pattern Analysis and Machine Intelligence (2022).

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