Remote Sensing Image Super-Resolution

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Multi-Task Partially Supervised Learning for Super-Resolution and Semantic Segmentation on Earth Observation data
Oct 5, 2026Hoàng-Ân Lê, Minh-Tan Pham, Solange Lemai-Chenevier +1Remote Sensing Image Segmentation Remote Sensing Image Super-Resolution
Universit´e Bretagne Sud, IRISA, UMR 6074, Vannes, France · Centre National d’Etudes Spatiales (CNES), Toulouse, France
ProSR: Semantic-Prototype-Guided Discrete Modeling for Physically Consistent SAR Super-Resolution
Sep 2, 2026Byoungwoo Kim, Munchurl KimRemote Sensing Image Super-Resolution
Korea Advanced Institute of Science and Technology, Daejeon, Republic of Korea
OGG-FR: Orthogonal Gradient Gaming and Frequency Rectification for Unmanned Aerial Vehicle Infrared Image Super-Resolution
Aug 10, 2026Yongsong Huang, Qingzhong Wang, Xiaofeng Liu +3Remote Sensing Image Super-Resolution Multi-Objective Optimization
Tohoku University · Amazon Web Services · Yale University
RoughNet: Mapping Arctic Sea Ice Roughness Using Diffusion-Based Super-Resolution of Satellite Imagery
Jul 15, 2026Tessa Cannon, Michel Tsamados, Petru Manescu +5Remote Sensing Image Super-Resolution Remote Sensing
Department of Computer Science, University College London · Department of Earth Sciences, University College London · Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research, Bremerhaven, Germany +1
Recovering Cloud Microstructures with Cascaded Diffusion Inversion
Jul 6, 2026Hanan Gani, Guy Pulik, Daniel Rosenfeld +2Diffusion Model Inversion Diffusion Models for Image Restoration
Mohamed Bin Zayed University of Artificial Intelligence · University of California, San Diego · Hebrew University of Jerusalem
Air Quality Downscaling with Station-Guided Pseudo-Supervision
Jul 6, 2026Guorun Wang, Simone Foti, Andreas D. Demou +5Remote Sensing Image Super-Resolution Air Quality Prediction
Imperial College London, UK · The Cyprus Institute, Cyprus · Northeastern University London, UK +1
Mind the Gap: Quantifying the Domain Gap in Cross-Sensor Diffusion Super-Resolution
Jun 26, 2026Dawid Kopeć, Katarzyna Jabłońska, Wojciech Kozłowski +1Synthetic-to-Real Domain Adaptation Diffusion Models for Image Restoration
WUST, Wybrzeże Stanisława Wyspiańskiego 27, 50-370 Wrocław, Poland · Tooploox, Tęczowa 7, 53-601 Wrocław, Poland
GSPan: A Continuous Gaussian Primitive Representation for Arbitrary-Scale Pansharpening
Jun 16, 2026Fangyi Li, Xiaoyuan Yang, Yixiao Li +3Remote Sensing Image Super-Resolution Remote Sensing
Beihang University, School of Mathematical Sciences, Beijing, 102206, China · Tsinghua University, Department of Automation, Beijing, 100084, China · National Research Council - Institute of Methodologies for Environmental Analysis, CNR-IMAA, Tito, 85050, Italy
NGram-MoSE: Efficient Remote Sensing Super-Resolution via N-Gram Context and Mixture-of-Experts
Jun 7, 2026Yun-Hsuan Huang, Trong-An Bui, Chih-Hung ChuangOOD Generalization Remote Sensing Image Super-Resolution
Institute of Aerospace and Systems Engineering, National Taipei University of Technology, Taipei City, Taiwan.
Flow-based Gaussian Splatting for Continuous-Scale Remote Sensing Image Super-Resolution
May 21, 2026Jiangwei Mo, Xi Lu, Hanlin WuRemote Sensing Image Super-Resolution Image Super-Resolution
School of Information Science and Technology, Beijing Foreign Studies University, Beijing 100089, China
HyperBench: Standardizing and Scaling Synthetic Evaluation for Hyperspectral Super-Resolution
May 20, 2026Ritik Shah, Marco F. DuarteBenchmark Design Remote Sensing Image Super-Resolution
University of Massachusetts Amherst, MA 01003
Learning to Balance: Decoupled Siamese Diffusion Transformer for Reference-Based Remote Sensing Image Super-Resolution
May 18, 2026Bin Luo, Runmin Dong, Zhaoyang Luo +4Diffusion Models for Image Restoration Diffusion Transformer
Tsinghua Shenzhen International Graduate School, Shenzhen, China · Sun Yat-sen University, Zhuhai, China · Tsinghua University, Beijing, China +1
Spatial-Frequency Gated Swin Transformer for Remote Sensing Single-Image Super-Resolution
May 10, 2026Md Aminur Hossain, Parekh Valkesh, Ayush V. Patel +3Remote Sensing Image Understanding Vision Transformer
Space Applications Centre, ISRO, Ahmedabad, India · New L J Institute of Engineering and Technology, Ahmedabad, India · Pandit Deendayal Energy University, Gandhinagar, India +2
Multispectral Blind Image Super-Resolution for Standing Dead Tree Segmentation
May 4, 2026Mete Ahishali, Anis Ur Rahman, Einari Heinaro +2Remote Sensing Image Segmentation Unsupervised Domain Adaptation
Department of Forest Sciences, University of Helsinki, Finland · CSC – IT Center for Science Ltd., Espoo, Finland · KOKO Forest Ltd. +1
SlimDiffSR: Toward Lightweight and Efficient Remote Sensing Image Super-Resolution via Diffusion Model Distillation
May 4, 2026Ce Wang, Zhenyu Hu, Wanjie SunDiffusion Model Distillation Remote Sensing Image Super-Resolution
School of Remote Sensing and Information Engineering, Wuhan University; Wuhan 430079, China
Flow matching for Sentinel-2 super-resolution: implementation, application, and implications
May 1, 2026Dakota Hester, Vitor S. Martins, Lucas B. Ferreira +2Flow Matching Land Cover Classification
Department of Agricultural and Biological Engineering, Mississippi State University · North Mississippi Research and Extension Center, Mississippi State University
Beyond Visual Fidelity: Benchmarking Super-Resolution Models for Large-Scale Remote Sensing Imagery via Downstream Task Integration
May 1, 2026Zhili Li, Kangyang Chai, Zhihao Wang +6Remote Sensing Image Super-Resolution Remote Sensing
University of Maryland · University of Pittsburgh · Worcester Polytechnic Institute +1
Edge-Cloud Collaborative Reconstruction via Structure-Aware Latent Diffusion for Downstream Remote Sensing Perception
Apr 28, 2026Yun Li, Xianju LiDiffusion Models for Image Restoration Edge Computing
School of Computer Science, China University of Geosciences, Wuhan, Hubei, China.
The First Challenge on Remote Sensing Infrared Image Super-Resolution at NTIRE 2026: Benchmark Results and Method Overview
Apr 23, 2026Kai Liu, Haoyang Yue, Zeli Lin +65Remote Sensing Image Super-Resolution Remote Sensing
Self-Supervised Super-Resolution for Sentinel-5P Hyperspectral Images
Apr 19, 2026Hyam Omar Ali, Antoine Crosnier, Romain Abraham +3Self-Supervised Learning Remote Sensing Image Super-Resolution
Université d’Orléans, Université de Tours, CNRS, IDP, UMR 7013, Orléans, France · Faculty of Mathematical Sciences, University of Khartoum, Sudan · ENS Lyon, France +2
When Earth Foundation Models Meet Diffusion: An Application to Land Surface Temperature Super-Resolution
Apr 18, 2026Yiheng Chen, Zihui Ma, Peishi Jiang +6Diffusion Model Guidance Remote Sensing Image Super-Resolution
University of Alabama · Emory University · University of Michigan +2
SERA-H: Super-Resolution of Sentinel Time Series for Fine-Scale Canopy Height Mapping
Dec 19, 2025Thomas Boudras, Martin Schwartz, Rasmus Fensholt +6Remote Sensing Image Super-Resolution Remote Sensing
Laboratoire des Sciences du Climat et de l’Environnement (LSCE), CEA, CNRS, UVSQ, Université Paris-Saclay, Gif-sur-Yvette, France · Department of Geography and Geology, University of Copenhagen, Øster Voldgade 10, Copenhagen, DK-1350, Denmark · Kayros SAS, Paris, 75009, France +2

Oct 5, 2026, cs.CVJ/K move · Enter open · S save

Multi-Task Partially Supervised Learning for Super-Resolution and Semantic Segmentation on Earth Observation data

Hoàng-Ân Lê, Minh-Tan Pham, Solange Lemai-Chenevier, Daniel Greslou

Universit´e Bretagne Sud, IRISA, UMR 6074, Vannes, France · Centre National d’Etudes Spatiales (CNES), Toulouse, France

Remote Sensing Image Segmentation Remote Sensing Image Super-Resolution Multi-Task Learning

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Super-resolution and semantic segmentation are known to benefit one another, especially in the Earth observation context. However, learning both tasks in a joint model often requires both task annotations, which is impractical and expensive. In this paper, we study the multi-task partially supervised learning paradigm for both tasks, where each example is assumed to have only a single-task annotation. To that end, we examine two multi-task architectural variations, the sequential and shared variants, and then propose a hybrid variant and a re-projection loss to benefit from the shared representation and enforce image quality of super-resolution when training with semantic segmentation. Experiments show favorable results compared to the SOTA sequential variant. Source code will be published at https://github.com/lhoangan/munera.

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