activity
20162023
most citedDeep learning in remote sensing: a review

3.2k citations · 3.7k across the 26 of their papers we have counts for

collaborators

33 papers

cs.CV20235 cited

DAM-Net: Global Flood Detection from SAR Imagery Using Differential Attention Metric-Based Vision Transformers

Tamer Saleh, Xingxing Weng, Shimaa Holail +2

The detection of flooded areas using high-resolution synthetic aperture radar (SAR) imagery is a critical task with applications in crisis and disaster management, as well as envir…

cs.CV20232 cited

HGFormer: Hierarchical Grouping Transformer for Domain Generalized Semantic Segmentation

Jian Ding, Nan Xue, Gui-Song Xia +2

Current semantic segmentation models have achieved great success under the independent and identically distributed (i.i.d.) condition. However, in real-world applications, test dat…

cs.CV20231 cited

Self-Supervised Scene Dynamic Recovery from Rolling Shutter Images and Events

Yangguang Wang, Xiang Zhang, Mingyuan Lin +4

Scene Dynamic Recovery (SDR) by inverting distorted Rolling Shutter (RS) images to an undistorted high frame-rate Global Shutter (GS) video is a severely ill-posed problem due to t…

cs.CV20231 cited

Dynamic Coarse-to-Fine Learning for Oriented Tiny Object Detection

Chang Xu, Jian Ding, Jinwang Wang +4

Detecting arbitrarily oriented tiny objects poses intense challenges to existing detectors, especially for label assignment. Despite the exploration of adaptive label assignment in…

cs.CV2023

Recovering Continuous Scene Dynamics from A Single Blurry Image with Events

Zhangyi Cheng, Xiang Zhang, Lei Yu +3

This paper aims at demystifying a single motion-blurred image with events and revealing temporally continuous scene dynamics encrypted behind motion blurs. To achieve this end, an…

cs.CV2023

Learning to Super-Resolve Blurry Images with Events

Lei Yu, Bishan Wang, Xiang Zhang +4

Super-Resolution from a single motion Blurred image (SRB) is a severely ill-posed problem due to the joint degradation of motion blurs and low spatial resolution. In this paper, we…