20 citations · 74 across the 14 of their papers we have counts for
14 papers
DR-Tune: Improving Fine-tuning of Pretrained Visual Models by Distribution Regularization with Semantic Calibration
Nan Zhou, Jiaxin Chen, Di Huang
The visual models pretrained on large-scale benchmarks encode general knowledge and prove effective in building more powerful representations for downstream tasks. Most existing ap…
Adaptive Sparse Convolutional Networks with Global Context Enhancement for Faster Object Detection on Drone Images
Bowei Du, Yecheng Huang, Jiaxin Chen +1
Object detection on drone images with low-latency is an important but challenging task on the resource-constrained unmanned aerial vehicle (UAV) platform. This paper investigates o…
OcTr: Octree-based Transformer for 3D Object Detection
Chao Zhou, Yanan Zhang, Jiaxin Chen +1
A key challenge for LiDAR-based 3D object detection is to capture sufficient features from large scale 3D scenes especially for distant or/and occluded objects. Albeit recent effor…
RGB-D Grasp Detection via Depth Guided Learning with Cross-modal Attention
Ran Qin, Haoxiang Ma, Boyang Gao +1
Planar grasp detection is one of the most fundamental tasks to robotic manipulation, and the recent progress of consumer-grade RGB-D sensors enables delivering more comprehensive f…
Towards Scale Balanced 6-DoF Grasp Detection in Cluttered Scenes
Haoxiang Ma, Di Huang
In this paper, we focus on the problem of feature learning in the presence of scale imbalance for 6-DoF grasp detection and propose a novel approach to especially address the diffi…
Representation Learning for Compressed Video Action Recognition via Attentive Cross-modal Interaction with Motion Enhancement
Bing Li, Jiaxin Chen, Dongming Zhang +2
Compressed video action recognition has recently drawn growing attention, since it remarkably reduces the storage and computational cost via replacing raw videos by sparsely sample…
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…
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…
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…
UFPMP-Det: Toward Accurate and Efficient Object Detection on Drone Imagery
Yecheng Huang, Jiaxin Chen, Di Huang
This paper proposes a novel approach to object detection on drone imagery, namely Multi-Proxy Detection Network with Unified Foreground Packing (UFPMP-Det). To deal with the numero…
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…
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…
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…
Image Inpainting via Conditional Texture and Structure Dual Generation
Xiefan Guo, Hongyu Yang, Di Huang
Deep generative approaches have recently made considerable progress in image inpainting by introducing structure priors. Due to the lack of proper interaction with image texture du…