Exploiting Completeness and Uncertainty of Pseudo Labels for Weakly
Supervised Video Anomaly Detection

Exploiting Completeness and Uncertainty of Pseudo Labels for Weakly Supervised Video Anomaly Detection

8 December 2022

Guorong Li

Ming-Hsuan Yang

Papers citing "Exploiting Completeness and Uncertainty of Pseudo Labels for Weakly Supervised Video Anomaly Detection"

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 15 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 34 6 0 09 Sep 2024
A Lightweight Video Anomaly Detection Model with Weak Supervision and Adaptive Instance Selection Yang Wang Jiaogen Zhou Jihong Guan 13 3 0 09 Oct 2023
In Defense of Pseudo-Labeling: An Uncertainty-Aware Pseudo-label Selection Framework for Semi-Supervised Learning Mamshad Nayeem Rizve Kevin Duarte Y. S. Rawat M. Shah 200 501 0 15 Jan 2021
Confidence Regularized Self-Training Yang Zou Zhiding Yu Xiaofeng Liu B. Kumar Jinsong Wang 207 783 0 26 Aug 2019
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 247 9,042 0 06 Jun 2015