73 citations · 105 across the 13 of their papers we have counts for
13 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…
SHREC'22 Track: Sketch-Based 3D Shape Retrieval in the Wild
Jie Qin, Shuaihang Yuan, Jiaxin Chen +22
Sketch-based 3D shape retrieval (SBSR) is an important yet challenging task, which has drawn more and more attention in recent years. Existing approaches address the problem in a r…
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…
Learning Multi-Granular Hypergraphs for Video-Based Person Re-Identification
Yichao Yan, Jie Qin1, Jiaxin Chen +4
Video-based person re-identification (re-ID) is an important research topic in computer vision. The key to tackling the challenging task is to exploit both spatial and temporal clu…
Learning Multi-Attention Context Graph for Group-Based Re-Identification
Yichao Yan, Jie Qin, Bingbing Ni +6
Learning to re-identify or retrieve a group of people across non-overlapped camera systems has important applications in video surveillance. However, most existing methods focus on…
Auto-Encoding Twin-Bottleneck Hashing
Yuming Shen, Jie Qin, Jiaxin Chen +5
Conventional unsupervised hashing methods usually take advantage of similarity graphs, which are either pre-computed in the high-dimensional space or obtained from random anchor po…
Embarrassingly Simple Binary Representation Learning
Yuming Shen, Jie Qin, Jiaxin Chen +2
Recent binary representation learning models usually require sophisticated binary optimization, similarity measure or even generative models as auxiliaries. However, one may wonder…
Deep Cross-modality Adaptation via Semantics Preserving Adversarial Learning for Sketch-based 3D Shape Retrieval
Jiaxin Chen, Yi Fang
Due to the large cross-modality discrepancy between 2D sketches and 3D shapes, retrieving 3D shapes by sketches is a significantly challenging task. To address this problem, we pro…