Browse State-of-the-Art › Point-interactive Image Colorization
Point-interactive Image Colorization
4 papers with code · 3 benchmarks · 3 datasets archive 2025-07-28
Point-interactive colorization is a task of colorizing images given user-guided clicks containing colors (a.k.a color hints). Unlike unconditional image colorization, which is an underdetermined problem by nature, point-interactive colorization aims to generate images containing specific colors given by the user.
Point-interactive colorization is evaluated by providing simulated user hints from the groundtruth color image. Following the iColoriT protocol, user hints have a size of 2x2 pixels and color is given as the average color within the 2x2 pixels.
Description from the archive 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 |
|---|---|---|---|---|---|
| Oxford 102 Flowers (7 rows) | iColoriT | iColoriT: Towards Propagating Local Hint to the Right Region in... | code | — | Compare |
| CUB-200-2011 (7 rows) | iColoriT | iColoriT: Towards Propagating Local Hint to the Right Region in... | code | — | Compare |
| ImageNet ctest10k (4 rows) | iColoriT | iColoriT: Towards Propagating Local Hint to the Right Region in... | code | — | 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.
Parent tasks archive 2025-07-28
Most implemented papers archive 2025-07-28
4 shown of 4 papers with code (4 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.
-
8 May 2017 3 repositories listedThe system directly maps a grayscale image, along with sparse, local user "hints" to an output colorization with a Convolutional Neural Network (CNN).
-
21 May 2020 2 repositories listed Syntology ran 0 of 7 samples · 7 unverifiedPrevious methods leverage the deep neural network to map input grayscale images to plausible color outputs directly.
-
14 Jul 2022 1 repository listedIt is essential for point-interactive colorization methods to appropriately propagate user-provided colors (i.
-
17 May 2019 1 repository listedIn addition to image filtering, we further show that the SWF principle can be extended to other applications involving the use of a local window.
Syntology lines on 1 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