Deep Anomaly Discovery From Unlabeled Videos via Normality Advantage and Self-Paced Refinement

4 August 2021

Papers citing "Deep Anomaly Discovery From Unlabeled Videos via Normality Advantage and Self-Paced Refinement"

6 / 6 papers shown

Title
ProDisc-VAD: An Efficient System for Weakly-Supervised Anomaly Detection in Video Surveillance Applications Tao Zhu Qi Yu Xinru Dong Shiyu Li Yue Liu Jinlong Jiang Lei Shu 24 0 0 04 May 2025
Deep Learning for Video Anomaly Detection: A Review Peng Wu Chengyu Pan Yuting Yan Guansong Pang Peng Wang Yanning Zhang VLM AI4TS 42 6 0 09 Sep 2024
Dynamic Data-Free Knowledge Distillation by Easy-to-Hard Learning Strategy Jingru Li Sheng Zhou Liangcheng Li Haishuai Wang Zhi Yu Jiajun Bu 21 14 0 29 Aug 2022
SSMTL++: Revisiting Self-Supervised Multi-Task Learning for Video Anomaly Detection Antonio Bărbălău Radu Tudor Ionescu Mariana-Iuliana Georgescu J. Dueholm B. Ramachandra Kamal Nasrollahi F. Khan T. Moeslund M. Shah ViT 17 69 0 16 Jul 2022
Curriculum Learning: A Survey Petru Soviany Radu Tudor Ionescu Paolo Rota N. Sebe ODL 70 338 0 25 Jan 2021
Joint Detection and Recounting of Abnormal Events by Learning Deep Generic Knowledge Ryota Hinami Tao Mei Shiníchi Satoh 108 227 0 26 Sep 2017