Browse State-of-the-Art › Photo Retouching
Photo Retouching
16 papers with code · 3 benchmarks · 3 datasets archive 2025-07-28
Benchmarks archive 2025-07-28
3 leaderboard tables shown for this task, 3 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted.
| Dataset | Best model (first row in archive order) | Paper | Code | Syntology | Compare |
|---|---|---|---|---|---|
| MIT-Adobe 5k (5 rows) | MAXIM | MAXIM: Multi-Axis MLP for Image Processing | code | Syntology ran 27 of 46 samples · 19 unverified | Compare |
| MIT-Adobe 5k (1080p) (2 rows) | LPTN (L=3) | High-Resolution Photorealistic Image Translation in Real-Time: A... | code | Syntology ran 3 of 5 samples · 2 unverified | Compare |
| MIT-Adobe 5k (480p) (2 rows) | LPTN (L=3) | High-Resolution Photorealistic Image Translation in Real-Time: A... | code | Syntology ran 3 of 5 samples · 2 unverified | Compare |
Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.
Libraries
Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.
Datasets archive 2025-07-28
3 datasets whose archive record lists this task, ordered by the archive's paper count.
Subtasks archive 2025-07-28
No subtask under this task in the archive's task tree.
Most implemented papers archive 2025-07-28
16 shown of 16 papers with code (27 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.
-
12 Mar 2023 5 repositories listed Syntology ran 2 of 10 samples · 8 unverifiedWhen enhancing low-light images, many deep learning algorithms are based on the Retinex theory.
-
9 Jan 2022 3 repositories listed Syntology ran 27 of 46 samples · 19 unverifiedIn this work, we present a multi-axis MLP based architecture called MAXIM, that can serve as an efficient and flexible general-purpose vision backbone for image processing tasks.
-
29 Nov 2019 3 repositories listedWe present a novel approach to adjust global image properties such as colour, saturation, and luminance using human-interpretable image enhancement curves, inspired by the Photoshop curves tool.
-
16 Dec 2024 1 repository listedReal-world design tasks - such as picture book creation, film storyboard development using character sets, photo retouching, visual effects, and font transfer - are highly diverse and complex, requiring deep…
-
20 Jun 2023 1 repository listedMoreover, a NILUT can be extended to incorporate multiple styles into a single network with the ability to blend styles implicitly.
-
15 Mar 2023 1 repository listed Syntology ran 3 of 12 samples · 9 unverified · 12 pointer-only (licence)Therefore, there is a need for white-box approaches that produce satisfying results and enable users to conveniently edit their images simultaneously.
-
3 Oct 2022 1 repository listedOur method accurately transfers complex detail retouching edits.
-
18 Jul 2022 1 repository listedImage-adaptive lookup tables (LUTs) have achieved great success in real-time image enhancement tasks due to their high efficiency for modeling color transforms.
-
29 Apr 2022 1 repository listed Syntology ran 1 of 1 samples · 0 unverifiedThey adopt a sub-optimal uniform sampling point allocation, limiting the expressiveness of the learned LUTs since the (tri-)linear interpolation between uniform sampling points in the LUT transform might fail to model…
-
9 Mar 2022 1 repository listedBody reshaping is an important procedure in portrait photo retouching.
-
1 Jan 2022 1 repository listedThe network is mainly composed of two components: a context-aware local retouching layer (LRL) and an adaptive blend pyramid layer (BPL).
-
19 May 2021 1 repository listed Syntology ran 3 of 5 samples · 2 unverifiedExisting image-to-image translation (I2IT) methods are either constrained to low-resolution images or long inference time due to their heavy computational burden on the convolution of high-resolution feature maps.
-
19 May 2021 1 repository listed Syntology ran 0 of 7 samples · 7 unverifiedHRP requires that more attention should be paid to human regions, while GLC requires that a group of portrait photos should be retouched to a consistent tone.
-
1 Jan 2021 1 repository listedSTAR is a general architecture that can be easily adapted to different image enhancement tasks.
-
22 Sep 2020 1 repository listedThe base network acts like an MLP that processes each pixel independently and the condition network extracts the global features of the input image to generate a condition vector.
-
24 Dec 2014 1 repository listedMany photographic styles rely on subtle adjustments that depend on the image content and even its semantics.
Syntology lines on 6 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.
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