31 citations · 46 across the 5 of their papers we have counts for
6 papers
GUI Exploration Lab: Enhancing Screen Navigation in Agents via Multi-Turn Reinforcement Learning
Haolong Yan, Yeqing Shen, Xin Huang +9
With the rapid development of Large Vision Language Models, the focus of Graphical User Interface (GUI) agent tasks shifts from single-screen tasks to complex screen navigation cha…
M-DocSum: Do LVLMs Genuinely Comprehend Interleaved Image-Text in Document Summarization?
Haolong Yan, Kaijun Tan, Yeqing Shen +5
We investigate a critical yet under-explored question in Large Vision-Language Models (LVLMs): Do LVLMs genuinely comprehend interleaved image-text in the document? Existing docume…
LLA: Loss-aware Label Assignment for Dense Pedestrian Detection
Zheng Ge, Jianfeng Wang, Xin Huang +2
Label assignment has been widely studied in general object detection because of its great impact on detectors' performance. However, none of these works focus on label assignment i…
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…
PS-RCNN: Detecting Secondary Human Instances in a Crowd via Primary Object Suppression
Zheng Ge, Zequn Jie, Xin Huang +2
Detecting human bodies in highly crowded scenes is a challenging problem. Two main reasons result in such a problem: 1). weak visual cues of heavily occluded instances can hardly p…