activity
20232026
most citedRank-DETR for High Quality Object Detection

25 citations · 29 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CV2026

Bridging the RGB-IR Gap: Consensus and Discrepancy Modeling for Text-Guided Multispectral Detection

Jiaqi Wu, Zhen Wang, Enhao Huang +5

Text-guided multispectral object detection uses text semantics to guide semantic-aware cross-modal interaction between RGB and IR for more robust perception. However, notable limit…

cs.CV2024

Exploring contextual modeling with linear complexity for point cloud segmentation

Yong Xien Chng, Xuchong Qiu, Yizeng Han +3

Point cloud segmentation is an important topic in 3D understanding that has traditionally has been tackled using either the CNN or Transformer. Recently, Mamba has emerged as a pro…

cs.CV2024★ 2 cited

2023 Low-Power Computer Vision Challenge (LPCVC) Summary

Leo Chen, Benjamin Boardley, Ping Hu +27

This article describes the 2023 IEEE Low-Power Computer Vision Challenge (LPCVC). Since 2015, LPCVC has been an international competition devoted to tackling the challenge of compu…

cs.CV2024★ 1 cited

GRA: Detecting Oriented Objects through Group-wise Rotating and Attention

Jiangshan Wang, Yifan Pu, Yizeng Han +4

Oriented object detection, an emerging task in recent years, aims to identify and locate objects across varied orientations. This requires the detector to accurately capture the or…

cs.CV2023★ 25 cited

Rank-DETR for High Quality Object Detection

Yifan Pu, Weicong Liang, Yiduo Hao +5

Modern detection transformers (DETRs) use a set of object queries to predict a list of bounding boxes, sort them by their classification confidence scores, and select the top-ranke…

cs.CV2023★ 1 cited

Fine-grained Recognition with Learnable Semantic Data Augmentation

Yifan Pu, Yizeng Han, Yulin Wang +3

Fine-grained image recognition is a longstanding computer vision challenge that focuses on differentiating objects belonging to multiple subordinate categories within the same meta…