Papers › NeurOp-Diff:Continuous Remote Sensing Image Super-Resolution via Neural Operator Diffusion

NeurOp-Diff:Continuous Remote Sensing Image Super-Resolution via Neural Operator Diffusion

15 Jan 2025arXiv:2501.09054archive 2025-07-28

Zihao Xu, Yuzhi Tang, Bowen Xu, Qingquan Li

Most publicly accessible remote sensing data suffer from low resolution, limiting their practical applications. To address this, we propose a diffusion model guided by neural operators for continuous remote sensing image super-resolution (NeurOp-Diff). Neural operators are used to learn resolution representations at arbitrary scales, encoding low-resolution (LR) images into high-dimensional features, which are then used as prior conditions to guide the diffusion model for denoising. This effectively addresses the artifacts and excessive smoothing issues present in existing super-resolution (SR) methods, enabling the generation of high-quality, continuous super-resolution images. Specifically, we adjust the super-resolution scale by a scaling factor s, allowing the model to adapt to different super-resolution magnifications. Furthermore, experiments on multiple datasets demonstrate the effectiveness of NeurOp-Diff. Our code is available at https://github.com/zerono000/NeurOp-Diff.

PaperPDFCodeCode Syntology ran

In Syntology Open this paper in Syntology's Atlas, the map of the papers in Syntology's graph and their citations.

For agents, Syntology's MCP tool lists every function and class Syntology harvested from this paper and whether it ran (how to connect): get_harvested_code_for_paper(arxiv_id="2501.09054")

Code

Syntology Ran 9 of 9 code samples harvested from 1 repository linked to this paper; 0 have no recorded run. Of those that ran: 9 ran with no contract checked.

By repository: official repository: 9 samples from 1 repository, 9 ran. The run record, sample by sample. “Ran” means executed on a synthesized input, not that the code is correct or reproduces the paper.

zerono000/neurop-diff officialmentioned in paperpytorch report

Repository list and official/mentioned flags are the archive's, frozen 2025-07-28. Reachability, where shown, is from one Syntology probe window (2026-09-16 to 2026-09-18); repositories not probed show nothing. GitHub stars are not tracked.

Code Syntology ran Syntology

9 samples harvested; 9 ran; 0 honoured the contract we drafted; 0 have no recorded run. Read from Syntology's graph 2026-09-24; that is when this build read the record, not when the samples ran.

9ran

Licence: 9 of the 9 samples are pointer only, meaning Syntology does not serve that copy's text. This page shows no code text for any sample; each one links to its file in the repository.

Harvested from zerono000/NeurOp-Diff. “Ran” means the sample executed on a synthesized input. It does not mean the output is correct, and nothing here reproduces the paper's results. “Honoured” and “violated” refer to a contract Syntology drafted from the code itself; “our draft was wrong” and “fixture could not drive it” are failures of Syntology's instrument, not of the code.

Each sample ends with its code_sha256, Syntology's identity for that exact code. An agent fetches the stored sample with Syntology's MCP tool get_code(code_sha256="…") (how to connect); click an identity to copy that call.

Repository labels, per sample. official repository: The archive marks this repository official for the paper. named in the paper: The archive records that the paper mentions this repository; it is not marked official. community (archive-listed): In the archive's code links for this paper, not marked official and not recorded as mentioned in the paper. found in paper text by Syntology: Syntology found this repository in the paper's own text; whether it is the authors' implementation is not asserted. community: Not in the archive's code links for this paper; a community repository Syntology harvested. Samples from a repository marked official are listed first. Licence labels name the repository's licence as recorded at harvest. “Pointer only” means Syntology does not serve that copy's text, for one of four reasons: no licence file was found; the licence was not identified; the licence is recorded as permissive but that copy's record is not marked cleared; or the licence is outside the permissive list Syntology serves text under (MIT, Apache-2.0, BSD and similar). Some licences outside that list permit redistribution, such as WTFPL, and GPL-3.0 under its conditions; they are simply not on the list. Hover a licence label for the reason. File links open the file on GitHub at the default branch, which may have changed since the harvest.

Block zerono000/NeurOp-Diff/models/diffusion.py official repository ran no licence file found · pointer only · ef9719744d2f0aca · report
Downsample zerono000/NeurOp-Diff/models/diffusion.py official repository ran no licence file found · pointer only · 527a7a3a5a9a53a1 · report
FeatureWiseAffine zerono000/NeurOp-Diff/models/diffusion.py official repository ran fingerprinted no licence file found · pointer only · 61f66a959a9e39db · report
PositionalEncoding zerono000/NeurOp-Diff/models/diffusion.py official repository ran fingerprinted no licence file found · pointer only · a1e44c37337ab3bf · report
ResnetBlocWithAttn zerono000/NeurOp-Diff/models/diffusion.py official repository ran no licence file found · pointer only · 94a85790900edbbd · report
ResnetBlock zerono000/NeurOp-Diff/models/diffusion.py official repository ran no licence file found · pointer only · 973f65ebee1cf4e9 · report
SelfAttention zerono000/NeurOp-Diff/models/diffusion.py official repository ran fingerprinted no licence file found · pointer only · c8584d0a7fb92793 · report
UNet zerono000/NeurOp-Diff/models/diffusion.py official repository ran no licence file found · pointer only · 9680ce4472992f4b · report
Upsample zerono000/NeurOp-Diff/models/diffusion.py official repository ran no licence file found · pointer only · 07244ed6f1e08f5a · report

Tasks

DenoisingImage Super-ResolutionSuper-Resolution

Results from the paper archive 2025-07-28

No leaderboard rows for this paper in the archive.

Methods

Diffusion

Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections