4 citations · 8 across the 14 of their papers we have counts for
8 papers · 1 filter
Learning to Balance: Decoupled Siamese Diffusion Transformer for Reference-Based Remote Sensing Image Super-Resolution
Bin Luo, Runmin Dong, Zhaoyang Luo +4
Diffusion-based methods demonstrate significant potential for remote sensing image super-resolution at large scaling factors, particularly in reference-based super-resolution (RefS…
RS-Prune: Training-Free Data Pruning at High Ratios for Efficient Remote Sensing Diffusion Foundation Models
Fan Wei, Runmin Dong, Yushan Lai +8
Diffusion-based remote sensing (RS) generative foundation models are cruial for downstream tasks. However, these models rely on large amounts of globally representative data, which…
Task-Oriented Data Synthesis and Control-Rectify Sampling for Remote Sensing Semantic Segmentation
Yunkai Yang, Yudong Zhang, Kunquan Zhang +4
With the rapid progress of controllable generation, training data synthesis has become a promising way to expand labeled datasets and alleviate manual annotation in remote sensing…
WakeupUrban: Unsupervised Semantic Segmentation of Mid-20 century Urban Landscapes with Satellite Imagery
Tianxiang Hao, Lixian Zhang, Yingjia Zhang +4
Historical satellite imagery archive, such as Keyhole satellite data, offers rare insights into understanding early urban development and long-term transformation. However, severe…
Evidential Graph Contrastive Alignment for Source-Free Blending-Target Domain Adaptation
Juepeng Zheng, Yibin Wen, Jinxiao Zhang +2
In this paper, we firstly tackle a more realistic Domain Adaptation (DA) setting: Source-Free Blending-Target Domain Adaptation (SF-BTDA), where we can not access to source domain…
A-MAE: A spatial-temporal-spectral unified remote sensing pre-training method based on anchor-aware masked autoencoder
Lixian Zhang, Yi Zhao, Runmin Dong +10
Vast amounts of remote sensing (RS) data provide Earth observations across multiple dimensions, encompassing critical spatial, temporal, and spectral information which is essential…
FUSU: A Multi-temporal-source Land Use Change Segmentation Dataset for Fine-grained Urban Semantic Understanding
Shuai Yuan, Guancong Lin, Lixian Zhang +6
Fine urban change segmentation using multi-temporal remote sensing images is essential for understanding human-environment interactions in urban areas. Although there have been adv…
DeepLight: Reconstructing High-Resolution Observations of Nighttime Light With Multi-Modal Remote Sensing Data
Lixian Zhang, Runmin Dong, Shuai Yuan +4
Nighttime light (NTL) remote sensing observation serves as a unique proxy for quantitatively assessing progress toward meeting a series of Sustainable Development Goals (SDGs), suc…