most citedBoundary Guided Context Aggregation for Semantic Segmentation

20 citations · 34 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CV20224 cited

Entropy-based Active Learning for Object Detection with Progressive Diversity Constraint

Jiaxi Wu, Jiaxin Chen, Di Huang

Active learning is a promising alternative to alleviate the issue of high annotation cost in the computer vision tasks by consciously selecting more informative samples to label. A…

cs.CV20223 cited

Target-Relevant Knowledge Preservation for Multi-Source Domain Adaptive Object Detection

Jiaxi Wu, Jiaxin Chen, Mengzhe He +7

Domain adaptive object detection (DAOD) is a promising way to alleviate performance drop of detectors in new scenes. Albeit great effort made in single source domain adaptation, a…

cs.CV20224 cited

CAT-Det: Contrastively Augmented Transformer for Multi-modal 3D Object Detection

Yanan Zhang, Jiaxin Chen, Di Huang

In autonomous driving, LiDAR point-clouds and RGB images are two major data modalities with complementary cues for 3D object detection. However, it is quite difficult to sufficient…

cs.CV202120 cited

Boundary Guided Context Aggregation for Semantic Segmentation

Haoxiang Ma, Hongyu Yang, Di Huang

The recent studies on semantic segmentation are starting to notice the significance of the boundary information, where most approaches see boundaries as the supplement of semantic…

cs.CV2021

PR-GCN: A Deep Graph Convolutional Network with Point Refinement for 6D Pose Estimation

Guangyuan Zhou, Huiqun Wang, Jiaxin Chen +1

RGB-D based 6D pose estimation has recently achieved remarkable progress, but still suffers from two major limitations: (1) ineffective representation of depth data and (2) insuffi…

cs.SI20213 cited

Recurrent Graph Neural Networks for Rumor Detection in Online Forums

Di Huang, Jacob Bartel, John Palowitch

The widespread adoption of online social networks in daily life has created a pressing need for effectively classifying user-generated content. This work presents techniques for cl…