Low-light Image Deblurring and Enhancement

Benchmarks archive 2025-07-28

1 leaderboard table shown for this task, 1 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.

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

2 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

3 shown of 3 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.

• Retinexformer: One-stage Retinex-based Transformer for Low-light Image Enhancement
  12 Mar 2023 5 repositories listed Syntology ran 2 of 10 samples · 8 unverified
  When enhancing low-light images, many deep learning algorithms are based on the Retinex theory.
• You Only Need One Color Space: An Efficient Network for Low-light Image Enhancement
  8 Feb 2024 1 repository listed
  Further, we design a novel Color and Intensity Decoupling Network (CIDNet) with two branches dedicated to processing the decoupled image brightness and color in the HVI space.
• LEDNet: Joint Low-light Enhancement and Deblurring in the Dark
  7 Feb 2022 1 repository listed Syntology ran 4 of 7 samples · 3 unverified · 7 pointer-only (licence)
  With the pipeline, we present the first large-scale dataset for joint low-light enhancement and deblurring.

Syntology lines on 2 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.