activity
20232026
most citedPanBench: Towards High-Resolution and High-Performance Pansharpening

2 citations · 3 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CV2026

Toward Stable Semi-Supervised Remote Sensing Segmentation via Co-Guidance and Co-Fusion

Yi Zhou, Xuechao Zou, Shun Zhang +7

Semi-supervised remote sensing (RS) image semantic segmentation offers a promising solution to alleviate the burden of exhaustive annotation, yet it fundamentally struggles with ps…

cs.CV2025

Dynamic Dictionary Learning for Remote Sensing Image Segmentation

Xuechao Zou, Yue Li, Shun Zhang +5

Remote sensing image segmentation faces persistent challenges in distinguishing morphologically similar categories and adapting to diverse scene variations. While existing methods…

cs.CV2025

Knowledge Transfer and Domain Adaptation for Fine-Grained Remote Sensing Image Segmentation

Shun Zhang, Xuechao Zou, Kai Li +4

Fine-grained remote sensing image segmentation is essential for accurately identifying detailed objects in remote sensing images. Recently, vision transformer models (VTMs) pre-tra…

cs.CV2024★ 1 cited

Adapting Vision Foundation Models for Robust Cloud Segmentation in Remote Sensing Images

Xuechao Zou, Shun Zhang, Kai Li +5

Cloud segmentation is a critical challenge in remote sensing image interpretation, as its accuracy directly impacts the effectiveness of subsequent data processing and analysis. Re…

cs.CV2024

A Parallel Attention Network for Cattle Face Recognition

Jiayu Li, Xuechao Zou, Shiying Wang +3

Cattle face recognition holds paramount significance in domains such as animal husbandry and behavioral research. Despite significant progress in confined environments, applying th…

cs.CV2023★ 2 cited

PanBench: Towards High-Resolution and High-Performance Pansharpening

Shiying Wang, Xuechao Zou, Kai Li +2

Pansharpening, a pivotal task in remote sensing, involves integrating low-resolution multispectral images with high-resolution panchromatic images to synthesize an image that is bo…