Papers › Efficient and Explicit Modelling of Image Hierarchies for Image Restoration

Efficient and Explicit Modelling of Image Hierarchies for Image Restoration

1 Mar 2023CVPR 2023 1arXiv:2303.00748archive 2025-07-28

Yawei Li, Yuchen Fan, Xiaoyu Xiang, Denis Demandolx, Rakesh Ranjan, Radu Timofte, Luc van Gool

The aim of this paper is to propose a mechanism to efficiently and explicitly model image hierarchies in the global, regional, and local range for image restoration. To achieve that, we start by analyzing two important properties of natural images including cross-scale similarity and anisotropic image features. Inspired by that, we propose the anchored stripe self-attention which achieves a good balance between the space and time complexity of self-attention and the modelling capacity beyond the regional range. Then we propose a new network architecture dubbed GRL to explicitly model image hierarchies in the Global, Regional, and Local range via anchored stripe self-attention, window self-attention, and channel attention enhanced convolution. Finally, the proposed network is applied to 7 image restoration types, covering both real and synthetic settings. The proposed method sets the new state-of-the-art for several of those. Code will be available at https://github.com/ofsoundof/GRL-Image-Restoration.git.

PaperPDFConference PDFCodeCode 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="2303.00748")

Code

Syntology Ran 4 of 12 code samples harvested from 1 repository linked to this paper; 8 have no recorded run. Of those that ran: 2 ran · our draft was wrong; 2 ran with no contract checked.

By repository: official repository: 12 samples from 1 repository, 4 ran. The run record, sample by sample. “Ran” means executed on a synthesized input, not that the code is correct or reproduces the paper.

ofsoundof/grl-image-restoration officialmentioned in paperpytorchMIT 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

12 samples harvested; 4 ran; 0 honoured the contract we drafted; 8 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.

2ran · our draft was wrong
2ran
8unverified

Licence: 0 of the 12 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 ofsoundof/GRL-Image-Restoration. “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.

default_conv ofsoundof/GRL-Image-Restoration/models/common/common_edsr.py official repository ran · our draft was wrong MIT (permissive) · 8b0e794d4d8f9b13 · report
get_image_paths ofsoundof/GRL-Image-Restoration/utils/utils_bsr/utils_image.py official repository ran MIT (permissive) · f9d4c247328f3337 · report
insert_bn ofsoundof/GRL-Image-Restoration/models/aux_archs/vgg.py official repository ran · our draft was wrong MIT (permissive) · 5360d45b71ae2bb1 · report
is_image_file ofsoundof/GRL-Image-Restoration/utils/utils_bsr/utils_image.py official repository ran MIT (permissive) · 226f6afcd57ff476 · report
is_image_file ofsoundof/GRL-Image-Restoration/utils/image_utils.py official repository unverified MIT (permissive) · d8709f460c3945ff · report
is_numpy_file ofsoundof/GRL-Image-Restoration/utils/image_utils.py official repository unverified MIT (permissive) · 2e6c9cf740755d88 · report
is_png_file ofsoundof/GRL-Image-Restoration/utils/image_utils.py official repository unverified MIT (permissive) · 61540a6c08cb232a · report
modcrop ofsoundof/GRL-Image-Restoration/utils/utils_image.py official repository unverified MIT (permissive) · 5ccdf73de87b7bf0 · report
patches_from_image ofsoundof/GRL-Image-Restoration/utils/utils_bsr/utils_image.py official repository unverified MIT (permissive) · 3984b3ec31e90ef0 · report
shave ofsoundof/GRL-Image-Restoration/utils/utils_image.py official repository unverified MIT (permissive) · 0455799ef89f3e08 · report
tensor_round ofsoundof/GRL-Image-Restoration/utils/utils_image.py official repository unverified MIT (permissive) · 5d49a4c5c692b24f · report
tv_loss ofsoundof/GRL-Image-Restoration/losses/losses.py official repository unverified MIT (permissive) · 9560f94a99c0322b · report

Tasks

Image DeblurringImage Defocus DeblurringImage RestorationImage Super-Resolution

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
Image Deblurring GoPro GRL PSNR 33.93 #10 of 55 Archive leaderboard report
Image Deblurring GoPro GRL Params (M) 19.81 #10 of 55 Archive leaderboard report
Image Deblurring GoPro GRL SSIM 0.968 #10 of 55 Archive leaderboard report

Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.

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