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"

10 / 10 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
Frequency-Guided Diffusion Model with Perturbation Training for Skeleton-Based Video Anomaly Detection Xiaofeng Tan Hongsong Wang Xin Geng Liang Wang DiffM AAML VGen 86 0 0 04 Dec 2024
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
Open-World Semantic Segmentation Including Class Similarity Matteo Sodano Federico Magistri Lucas Nunes Jens Behley C. Stachniss VLM 42 8 0 12 Mar 2024
Interleaving One-Class and Weakly-Supervised Models with Adaptive Thresholding for Unsupervised Video Anomaly Detection Yongwei Nie Hao Huang Chengjiang Long Qing Zhang Pradipta Maji Hongmin Cai 31 1 0 24 Jan 2024
Video Anomaly Detection and Explanation via Large Language Models Hui Lv Qianru Sun 31 20 0 11 Jan 2024
A Lightweight Video Anomaly Detection Model with Weak Supervision and Adaptive Instance Selection Yang Wang Jiaogen Zhou Jihong Guan 29 4 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 217 508 0 15 Jan 2021
Confidence Regularized Self-Training Yang Zou Zhiding Yu Xiaofeng Liu B. Kumar Jinsong Wang 230 789 0 26 Aug 2019
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 285 9,136 0 06 Jun 2015