4 citations · 12 across the 4 of their papers we have counts for
11 papers · 1 filter
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…
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…