11 citations · 11 across the 2 of their papers we have counts for
2 papers
cs.LG2026
RGLD: Randomized Global-Local Density Estimation for Tabular Anomaly Detection
Quanling Zhao, Jiaying Yang, Ye Tian +5
Unsupervised tabular anomaly detection requires methods that are accurate, robust across heterogeneous datasets, and computationally efficient. Classical statistical detectors are…
cs.CV2020★ 11 cited
Adaptive Mixture Regression Network with Local Counting Map for Crowd Counting
Xiyang Liu, Jie Yang, Wenrui Ding
The crowd counting task aims at estimating the number of people located in an image or a frame from videos. Existing methods widely adopt density maps as the training targets to op…