activity
20202026
most citedLocalizing Anomalies from Weakly-Labeled Videos

193 citations · 193 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV2026

Learning to Label: A Reinforced Self-Evolving Framework for Semi-supervised Referring Expression Segmentation

Runlong Cao, Ying Zang, Chuanwei Zhou +4

Semi-supervised referring expression segmentation (SS-RES) aims to achieve precise pixel-level language grounding under limited annotation, yet suffers from limited supervision and…

cs.CV2025

Beyond One Shot, Beyond One Perspective: Cross-View and Long-Horizon Distillation for Better LiDAR Representations

Xiang Xu, Lingdong Kong, Song Wang +2

LiDAR representation learning aims to extract rich structural and semantic information from large-scale, readily available datasets, reducing reliance on costly human annotations.…

cs.CV2023

SGNet: Salient Geometric Network for Point Cloud Registration

Qianliang Wu, Yaqing Ding, Lei Luo +5

Point Cloud Registration (PCR) is a critical and challenging task in computer vision. One of the primary difficulties in PCR is identifying salient and meaningful points that exhib…

cs.LG2023

Structure-Sensitive Graph Dictionary Embedding for Graph Classification

Guangbu Liu, Tong Zhang, Xudong Wang +3

Graph structure expression plays a vital role in distinguishing various graphs. In this work, we propose a Structure-Sensitive Graph Dictionary Embedding (SS-GDE) framework to tran…

cs.CV2020★ 193 cited

Localizing Anomalies from Weakly-Labeled Videos

Hui Lv, Chuanwei Zhou, Chunyan Xu +2

Video anomaly detection under video-level labels is currently a challenging task. Previous works have made progresses on discriminating whether a video sequencecontains anomalies.…