85 citations · 226 across the 11 of their papers we have counts for
19 papers
Multiple Object Tracking Challenge Technical Report for Team MT_IoT
Feng Yan, Zhiheng Li, Weixin Luo +4
This is a brief technical report of our proposed method for Multiple-Object Tracking (MOT) Challenge in Complex Environments. In this paper, we treat the MOT task as a two-stage ta…
Expansion and Shrinkage of Localization for Weakly-Supervised Semantic Segmentation
Jinlong Li, Zequn Jie, Xu Wang +2
Generating precise class-aware pseudo ground-truths, a.k.a, class activation maps (CAMs), is essential for weakly-supervised semantic segmentation. The original CAM method usually…
Weakly Supervised Semantic Segmentation via Progressive Patch Learning
Jinlong Li, Zequn Jie, Xu Wang +3
Most of the existing semantic segmentation approaches with image-level class labels as supervision, highly rely on the initial class activation map (CAM) generated from the standar…
Two-stage Visual Cues Enhancement Network for Referring Image Segmentation
Yang Jiao, Zequn Jie, Weixin Luo +4
Referring Image Segmentation (RIS) aims at segmenting the target object from an image referred by one given natural language expression. The diverse and flexible expressions as wel…
Delving into the Imbalance of Positive Proposals in Two-stage Object Detection
Zheng Ge, Zequn Jie, Xin Huang +2
Imbalance issue is a major yet unsolved bottleneck for the current object detection models. In this work, we observe two crucial yet never discussed imbalance issues. The first imb…
NMS by Representative Region: Towards Crowded Pedestrian Detection by Proposal Pairing
Xin Huang, Zheng Ge, Zequn Jie +1
Although significant progress has been made in pedestrian detection recently, pedestrian detection in crowded scenes is still challenging. The heavy occlusion between pedestrians i…