87 citations · 119 across the 7 of their papers we have counts for
7 papers
MM-DETR: An Efficient Multimodal Detection Transformer with Mamba-Driven Dual-Granularity Fusion and Frequency-Aware Modality Adapters
Jianhong Han, Yupei Wang, Yuan Zhang +1
Multimodal remote sensing object detection aims to achieve more accurate and robust perception under challenging conditions by fusing complementary information from different modal…
VFM-Guided Semi-Supervised Detection Transformer under Source-Free Constraints for Remote Sensing Object Detection
Jianhong Han, Yupei Wang, Liang Chen
Unsupervised domain adaptation methods have been widely explored to bridge domain gaps. However, in real-world remote-sensing scenarios, privacy and transmission constraints often…
Style-Adaptive Detection Transformer for Single-Source Domain Generalized Object Detection
Jianhong Han, Yupei Wang, Liang Chen
Single-source domain generalization (SDG) in object detection aims to develop a detector using only source domain data that generalizes well to unseen target domains. Existing meth…
DATR: Unsupervised Domain Adaptive Detection Transformer with Dataset-Level Adaptation and Prototypical Alignment
Jianhong Han, Liang Chen, Yupei Wang
Object detectors frequently encounter significant performance degradation when confronted with domain gaps between collected data (source domain) and data from real-world applicati…
MS-Net: A Multi-modal Self-supervised Network for Fine-Grained Classification of Aircraft in SAR Images
Bingying Yue, Jianhao Li, Hao Shi +2
Synthetic aperture radar (SAR) imaging technology is commonly used to provide 24-hour all-weather earth observation. However, it still has some drawbacks in SAR target classificati…
SSAP: Single-Shot Instance Segmentation With Affinity Pyramid
Naiyu Gao, Yanhu Shan, Yupei Wang +4
Recently, proposal-free instance segmentation has received increasing attention due to its concise and efficient pipeline. Generally, proposal-free methods generate instance-agnost…
Deep Crisp Boundaries: From Boundaries to Higher-level Tasks
Yupei Wang, Xin Zhao, Yin Li +1
Edge detection has made significant progress with the help of deep Convolutional Networks (ConvNet). These ConvNet based edge detectors have approached human level performance on s…