5 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…
Earth-Adapter: Bridge the Geospatial Domain Gaps with Mixture of Frequency Adaptation
Xiaoxing Hu, Ziyang Gong, Yupei Wang +8
Parameter-Efficient Fine-Tuning (PEFT) is a technique that allows us to adapt powerful Foundation Models (FMs) to diverse downstream tasks while preserving and unleashing their inh…
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…