NR-IQA

Description from the archive archive 2025-07-28; Papers-with-Code links inside it are rewritten to this site.

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

8 shown of 8 papers with code (50 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.

• DGIQA: Depth-guided Feature Attention and Refinement for Generalizable Image Quality Assessment
  29 May 2025 1 repository listed
  A long-held challenge in no-reference image quality assessment (NR-IQA) learning from human subjective perception is the lack of objective generalization to unseen natural distortions.
• VisualQuality-R1: Reasoning-Induced Image Quality Assessment via Reinforcement Learning to Rank
  20 May 2025 1 repository listed Syntology ran 1 of 14 samples · 13 unverified
  In this paper, we introduce VisualQuality-R1, a reasoning-induced no-reference IQA (NR-IQA) model, and we train it with reinforcement learning to rank, a learning algorithm tailored to the intrinsically relative nature…
• Exploring Semantic Feature Discrimination for Perceptual Image Super-Resolution and Opinion-Unaware No-Reference Image Quality Assessment
  25 Mar 2025 1 repository listed Syntology ran 2 of 3 samples · 1 unverified · 3 pointer-only (licence)
  With both Feat-D and TG-D, our SFD can effectively distinguish between the semantic feature distributions of low-quality and high-quality images, encouraging SRN to generate more realistic and semantic-relevant textures.
• Backdoor Attacks against No-Reference Image Quality Assessment Models via a Scalable Trigger
  10 Dec 2024 1 repository listed Syntology ran 3 of 12 samples · 9 unverified · 12 pointer-only (licence)
  To address these challenges, we shift our focus to another significant threat and present a novel poisoning-based backdoor attack against NR-IQA (BAIQA), allowing the attacker to manipulate the IQA model's output to any…
• AIM 2024 Challenge on UHD Blind Photo Quality Assessment
  24 Sep 2024 1 repository listed
  By pushing the boundaries of NR-IQA for high-resolution photos, the UHD-IQA Challenge aims to stimulate the development of practical models that can keep pace with the rapidly evolving landscape of digital photography.
• Attention Down-Sampling Transformer, Relative Ranking and Self-Consistency for Blind Image Quality Assessment
  11 Sep 2024 1 repository listed
  The no-reference image quality assessment is a challenging domain that addresses estimating image quality without the original reference.
• UHD-IQA Benchmark Database: Pushing the Boundaries of Blind Photo Quality Assessment
  25 Jun 2024 1 repository listed
  We introduce a novel Image Quality Assessment (IQA) dataset comprising 6073 UHD-1 (4K) images, annotated at a fixed width of 3840 pixels.
• Diffusion Model Based Visual Compensation Guidance and Visual Difference Analysis for No-Reference Image Quality Assessment
  22 Feb 2024 1 repository listed
  Firstly, we devise a new diffusion restoration network that leverages the produced enhanced image and noise-containing images, incorporating nonlinear features obtained during the denoising process of the diffusion…

Syntology lines on 3 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.