6 papers
SFR-Net: Learning Scale-Frustum Representations for Ultra-Wide Area Remote Sensing Image Segmentation
Chuyu Zhong, Keyan Chen, Qinzhe Yang +3
Pixel count and geographical coverage are two key characteristics of remote sensing images. Existing remote sensing image segmentation methods typically focus on images with either…
DynamicVis: Dynamic Visual Perception for Efficient Remote Sensing Foundation Models
Keyan Chen, Chenyang Liu, Bowen Chen +4
The advancement of RS technology has enabled high-resolution Earth observation; however, interpreting these images using modern VFMs remains a significant challenge. Unlike object-…
TaCo: Capturing Spatio-Temporal Semantic Consistency in Remote Sensing Change Detection
Han Guo, Chenyang Liu, Haotian Zhang +3
Remote sensing change detection (RSCD) aims to identify surface changes across bi-temporal satellite images. Most previous methods rely solely on mask supervision, which effectivel…
SeG-SR: Integrating Semantic Knowledge into Remote Sensing Image Super-Resolution via Vision-Language Model
Bowen Chen, Keyan Chen, Mohan Yang +2
High-resolution (HR) remote sensing imagery plays a vital role in a wide range of applications, including urban planning and environmental monitoring. However, due to limitations i…
RSRefSeg 2: Decoupling Referring Remote Sensing Image Segmentation with Foundation Models
Keyan Chen, Chenyang Liu, Bowen Chen +3
Referring Remote Sensing Image Segmentation provides a flexible and fine-grained framework for remote sensing scene analysis via vision-language collaborative interpretation. Curre…
Heterogeneous Mixture of Experts for Remote Sensing Image Super-Resolution
Bowen Chen, Keyan Chen, Mohan Yang +2
Remote sensing image super-resolution (SR) aims to reconstruct high-resolution remote sensing images from low-resolution inputs, thereby addressing limitations imposed by sensors a…