Fetching the paper…
Reading the bibliography…
Super-Resolution for remote sensing has the potential for huge impact on planet monitoring by producing accurate and realistic high resolution imagery on a frequent basis and a global scale.
Real-esrgan: Training real-world blind super-resolution with pure synthetic data
Xintao Wang, Liangbin Xie, Chao Dong, and Ying Shan · 1914
Earlier work this paper cites.
Image quality assessment: from error visibility to structural similarity
Zhou Wang, Alan Conrad Bovik, Hamid R. Sheikh, and Eero P. Simoncelli · 2004
Earlier work this paper cites.
Image super-resolution using deep convolutional networks
Chao Dong, Chen Change Loy, Kaiming He, and Xiaoou Tang · 2014
Earlier work this paper cites.
Remote Sensing Image Scene Classification: Benchmark and State of the Art
Gong Cheng, Junwei Han, and Xiaoqiang Lu · 2017
Earlier work this paper cites.
Performance enhancement of satellite image classification using a convolutional neural network
Noureldin Laban, Bassam Abdellatif, H. M. Ebied, Howida A. Shedeed, and Mohamed F. Tolba · 2017
Earlier work this paper cites.
Enhanced deep residual networks for single image super-resolution
Bee Lim, Sanghyun Son, Heewon Kim, Seungjun Nah, and Kyoung Mu Lee · 2017
Earlier work this paper cites.
Deep image- to-image transfer applied to resolution enhancement of sentinel-2 images
Mario Beaulieu, Samuel Foucher, Dan Haberman, and Colin Stewart · 2018
Earlier work this paper cites.
Functional Map of the World
Gordon Christie, Neil Fendley, James Wilson, and Ryan Mukherjee · 2018
Earlier work this paper cites.
Photorealistic video super resolution
Eduardo Pérez-Pellitero, Mehdi S. M. Sajjadi, Michael Hirsch, and Bernhard Scholkopf · 2018
Earlier work this paper cites.
Esrgan: Enhanced super-resolution generative adversarial networks
Xintao Wang, Ke Yu, Shixiang Wu, Jinjin Gu, Yihao Liu, Chao Dong, Chen Change Loy, Yu Qiao, and Xiaoou Tang · 2018
Earlier work this paper cites.
The unreasonable effectiveness of deep features as a perceptual metric
Richard Zhang, Phillip Isola, Alexei A. Efros, Eli Shechtman, and Oliver Wang · 2018
Earlier work this paper cites.
Residual dense network for image super-resolution
Yulun Zhang, Yapeng Tian, Yu Kong, Bineng Zhong, and Yun Raymond Fu · 2018
Earlier work this paper cites.
Satellite image super-resolution via multi-scale residual deep neural network
Tao Lu, Jiaming Wang, Yanduo Zhang, Zhongyuan Wang, and Junjun Jiang · 2019
Earlier work this paper cites.
Deepsum: Deep neural network for super-resolution of unregistered multitemporal images
Andrea Bordone Molini, Diego Valsesia, Giulia Fracastoro, and Enrico Magli · 2019
Earlier work this paper cites.
Super-resolution of proba-v images using convolutional neural networks
Marcus Märtens, Dario Izzo, Andrej Krzic, and Daniël Cox · 2019
Earlier work this paper cites.
Bigearthnet: A large-scale benchmark archive for remote sensing image understanding
Gencer Sumbul, Marcela Charfuelan, Begüm Demir, and Volker Markl · 2019
Earlier work this paper cites.
Fast and accurate multi-frame super-resolution of satellite images
Jérémy Anger, Thibaud Ehret, Carlo de Franchis, and G. Facciolo · 2020
Earlier work this paper cites.
Highres-net: Recursive fusion for multi-frame super-resolution of satellite imagery
Michel Deudon, Alfredo Kalaitzis, Israel Goytom, Md Rifat Arefin, Zhichao Lin, Kris Sankaran, Vincent Michalski, Samira Ebrahimi Kahou, Julien Cornebise, and Yoshua Bengio · 2020
Earlier work this paper cites.
Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and P. Abbeel · 2020
Earlier work this paper cites.
Urban land cover classification of high-resolution aerial imagery using a relation-enhanced multiscale convolutional network
Chun Liu, Doudou Zeng, Hangbin Wu, Yin Wang, Shoujun Jia, and Liang Xin · 2020
Earlier work this paper cites.
Massachusetts buildings dataset
Volodymyr Mnih · 2020
Earlier work this paper cites.
Fusion of deep and non-deep methods for fast super-resolution of satellite images
Gaurav Kumar Nayak, Saksham Jain, R. Venkatesh Babu, and Anirban Chakraborty · 2020
Cited alongside, same era.
A generative adversarial network approach for super-resolution of sentinel-2 satellite images
Ferdinand Pineda, Victor H. Andres Ayma, and César Beltrán · 2020
Cited alongside, same era.
Francesco Salvetti, Vittorio Mazzia, Aleem Khaliq, and Marcello Chiaberge · 2020
Cited alongside, same era.
Denoising diffusion implicit models
Jiaming Song, Chenlin Meng, and Stefano Ermon · 2020
Cited alongside, same era.
Improved srgan for remote sensing image superresolution across locations and sensors
Yingfei Xiong, Shanxin Guo, Jinsong Chen, Xinping Deng, Luyi Sun, Xiaorou Zheng, and Wenna Xu · 2020
Multimodal contrastive learning for remote sensing tasks
Umang Jain, Alex Wilson, and Varun Gulshan · 2022
Later among the works it cites.
Diffusion model with detail complement for super-resolution of remote sensing
Jinzhe Liu, Zhiqiang Yuan, Zhaoying Pan, Yiqun Fu, Li Liu, and Bin Lu · 2022
Later among the works it cites.
Fine crop classification in high resolution remote sensing based on deep learning
Tingyu Lu, Luhe Wan, and Lei Wang · 2022
Later among the works it cites.
Sen2venµs, a dataset for the training of sentinel-2 super-resolution algorithms
Julien Michel, Juan Vinasco-Salinas, Jordi Inglada, and Olivier Hagolle · 2022
Later among the works it cites.
Evaluation of srgan algorithm for superresolution of satellite imagery on different sensors
Jaskaran Singh Puri and Andre Kotze · 2022
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Deep burst super-resolution
Goutam Bhat, Martin Danelljan, Luc Van Gool, and Radu Timofte · 2021
Cited alongside, same era.
Rrsgan: Reference-based super-resolution for remote sensing image
Runmin Dong, Lixian Zhang, and Haohuan Fu · 2021
Cited alongside, same era.
Panoptic segmentation of satellite image time series with convolutional temporal attention networks
Vivien Sainte Fare Garnot and Loic Landrieu · 2021
Cited alongside, same era.
Spatial-temporal super-resolution of satellite imagery via conditional pixel synthesis
Yutong He, Dingjie Wang, Nicholas Lai, William Zhang, Chenlin Meng, M. Burke, D. Lobell, and Stefano Ermon · 2021
Cited alongside, same era.
Clipscore: A reference-free evaluation metric for image captioning
Jack Hessel, Ari Holtzman, Maxwell Forbes, Ronan Le Bras, and Yejin Choi · 2021
Cited alongside, same era.
Swin transformer: Hierarchical vision transformer using shifted windows
Ze Liu, Yutong Lin, Yue Cao, Han Hu, Yixuan Wei, Zheng Zhang, Stephen Lin, and Baining Guo · 2021
Cited alongside, same era.
Seasonal contrast: Unsupervised pre-training from uncurated remote sensing data
Oscar Mañas, Alexandre Lacoste, Xavier Giró i Nieto, David Vázquez, and Pau Rodríguez López · 2021
Cited alongside, same era.
Yi Wang, Nassim Ait Ali Braham, Zhitong Xiong, Chenying Liu, Conrad M. Albrecht, and Xiao Xiang Zhu · 2022
Later among the works it cites.
Te-sagan: An improved generative adversarial network for remote sensing super-resolution images
Yongyang Xu, Wei Luo, Anna Hu, Zhong Xie, Xuejing Xie, and Liufeng Tao · 2022
Later among the works it cites.
Tesr: Two-stage approach for enhancement and super-resolution of remote sensing images
Anas M. Ali, Bilel Benjdira, Anis Koubâa, Wadii Boulila, and Walid El Shafai · 2023
Closest in time.
Satlaspretrain: A large-scale dataset for remote sensing image understanding
Favyen Bastani, Piper Wolters, Ritwik Gupta, Joe Ferdinando, and Aniruddha Kembhavi · 2023
Closest in time.
Datacomp: In search of the next generation of multimodal datasets
Samir Yitzhak Gadre, Gabriel Ilharco, Alex Fang, Jonathan Hayase, Georgios Smyrnis, Thao Nguyen, Ryan Marten, Mitchell Wortsman, Dhruba Ghosh, Jieyu Zhang, Eyal Orgad, Rahim Entezari, Giannis Daras, Sarah Pratt, Vivek Ramanujan, Yonatan Bitton, Kalyani Marathe, Stephen Mussmann, Richard Vencu, Mehdi Cherti, Ranjay Krishna, Pang Wei Koh, Olga Saukh, Alexander J. Ratner, Shuran Song, Hannaneh Hajishirzi, Ali Farhadi, Romain Beaumont, Sewoong Oh, Alexandros G. Dimakis, Jenia Jitsev, Yair Carmon, Vaishaal Shankar, and Ludwig Schmidt · 2023
Closest in time.
Enhancing remote sensing image super-resolution with efficient hybrid conditional diffusion model
Lintao Han, Yuchen Zhao, Hengyi Lv, Yisa Zhang, Hailong Liu, Guoling Bi, and Qing Han · 2023
Closest in time.
Scaling up gans for text-to-image synthesis
Minguk Kang, Jun-Yan Zhu, Richard Zhang, Jaesik Park, Eli Shechtman, Sylvain Paris, and Taesung Park · 2023
Closest in time.
A real-world benchmark for sentinel-2 multi-image super-resolution
Pawel Kowaleczko, Tomasz Tarasiewicz, Maciej Ziaja, Daniel Kostrzewa, Jakub Nalepa, Przemyslaw Rokita, and Michal Kawulok · 2023
Closest in time.
Sr-feinr: Continuous remote sensing image super-resolution using feature-enhanced implicit neural representation
Jinming Luo, Lei Han, Xianjie Gao, Xiuping Liu, and Weiming M. Wang · 2023
Closest in time.
Change-aware sampling and contrastive learning for satellite images
Utkarsh Mall, Bharath Hariharan, and Kavita Bala · 2023
Closest in time.
Eva-clip: Improved training techniques for clip at scale
Quan Sun, Yuxin Fang, Ledell Yu Wu, Xinlong Wang, and Yue Cao · 2023
Closest in time.
An integrated deep learning and object-based image analysis approach for mapping debris-covered glaciers
Daniel Jack Thomas, Benjamin Aubrey Robson, and Adina E. Racoviteanu · 2023
Closest in time.
Multi-frame super-resolution of remote sensing images using attention-based gan models
Peijuan Wang and Elif Sertel · 2023
Closest in time.
Hu Xu, Saining Xie, Xiaoqing Ellen Tan, Po-Yao (Bernie) Huang, Russell Howes, Vasu Sharma, Shang-Wen Li, Gargi Ghosh, Luke Zettlemoyer, and Christoph Feichtenhofer · 2023
Closest in time.
Resshift: Efficient diffusion model for image super-resolution by residual shifting
Zongsheng Yue, Jianyi Wang, and Chen Change Loy · 2023
Closest in time.
Sigmoid loss for language image pre-training
Xiaohua Zhai, Basil Mustafa, Alexander Kolesnikov, and Lucas Beyer · 2023
Closest in time.