collaborators

10 papers

cs.CV2026

Graph-based Semantic Calibration Network for Unaligned UAV RGBT Image Semantic Segmentation and A Large-scale Benchmark

Fangqiang Fan, Zhicheng Zhao, Xiaoliang Ma +2

Fine-grained RGBT image semantic segmentation is crucial for all-weather unmanned aerial vehicle (UAV) scene understanding. However, UAV RGBT image semantic segmentation faces two…

eess.IV2026

Compositional-Degradation UAV Image Restoration: Conditional Decoupled MoE Network and A Benchmark

Jinquan Yan, Zhicheng Zhao, Zhengzheng Tu +3

UAV images are critical for applications such as large-area mapping, infrastructure inspection, and emergency response. However, in real-world flight environments, a single image i…

cs.CV2026

UAV traffic scene understanding: A regulation embedded multi-modal network and a unified benchmark

Yu Zhang, Zhicheng Zhao, Ze Luo +2

Traffic scene understanding from unmanned aerial vehicle (UAV) platforms is crucial for intelligent transportation systems due to its flexible deployment and wide-area monitoring c…

cs.CV2026

Physics-Constrained Cross-Resolution Enhancement Network for Optics-Guided Thermal UAV Image Super-Resolution

Zhicheng Zhao, Fengjiao Peng, Jinquan Yan +3

Optics-guided thermal UAV image super-resolution has attracted significant research interest due to its potential in all-weather monitoring applications. However, existing methods…

cs.CV2025

Learning Where to Focus: Density-Driven Guidance for Detecting Dense Tiny Objects

Zhicheng Zhao, Xuanang Fan, Lingma Sun +2

High-resolution remote sensing imagery increasingly contains dense clusters of tiny objects, the detection of which is extremely challenging due to severe mutual occlusion and limi…

cs.CV2025

Towards Robust Optical-SAR Object Detection under Missing Modalities: A Dynamic Quality-Aware Fusion Framework

Zhicheng Zhao, Yuancheng Xu, Andong Lu +2

Optical and Synthetic Aperture Radar (SAR) fusion-based object detection has attracted significant research interest in remote sensing, as these modalities provide complementary in…