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Yongchao Feng

4 accepted papers

2026

WaveC2R: Wavelet-Driven Coarse-to-Refined Hierarchical Learning for Radar Retrieval

AAAI 2026technical

Satellite-based radar retrieval methods are widely employed to fill coverage gaps in ground-based radar systems, especially in remote areas affected by terrain blockage and limited detection range. Existing methods predominantly rely on overly simplistic spatial-domain architectures constructed from

Cited by 0SourcePDFScholar
2025

OpenRSD: Towards Open-prompts for Object Detection in Remote Sensing Images

ICCV 2025poster

Remote sensing object detection has made significant progress, but most studies still focus on closed-set detection, limiting generalization across diverse datasets. Open-vocabulary object detection (OVD) provides a solution by leveraging multimodal associations between text prompts and visual featu…

2024

DSD-DA: Distillation-based Source Debiasing for Domain Adaptive Object Detection

ICML 2024poster

Though feature-alignment based Domain Adaptive Object Detection (DAOD) methods have achieved remarkable progress, they ignore the source bias issue, i.e., the detector tends to acquire more source-specific knowledge, impeding its generalization capabilities in the target domain. Furthermore, these m…

Cited by 2SourcePDFScholar
2024

MutDet: Mutually Optimizing Pre-training for Remote Sensing Object Detection

ECCV 2024poster

"Detection pre-training methods for the DETR series detector have been extensively studied in natural scenes, e.g., DETReg. However, the detection pre-training remains unexplored in remote sensing scenes. In existing pre-training methods, alignment between object embeddings extracted from a pre-trai…