Blind Image Quality Assessment

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

Benchmarks archive 2025-07-28

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Libraries

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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

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Parent tasks archive 2025-07-28

Most implemented papers archive 2025-07-28

6 shown of 6 papers with code (46 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.

• Taylor expansion-based Kolmogorov-Arnold network for blind image quality assessment
  27 May 2025 1 repository listed
  Kolmogorov-Arnold Network (KAN) has attracted growing interest for its strong function approximation capability.
• 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.
• No-Reference Image Quality Assessment with Global-Local Progressive Integration and Semantic-Aligned Quality Transfer
  7 Aug 2024 1 repository listed
  Accurate measurement of image quality without reference signals remains a fundamental challenge in low-level visual perception applications.
• 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.
• DDR: Exploiting Deep Degradation Response as Flexible Image Descriptor
  12 Jun 2024 1 repository listed Syntology ran 0 of 1 samples · 1 unverified · 1 pointer-only (licence)
  In this paper, we present Deep Degradation Response (DDR), a method to quantify changes in image deep features under varying degradation conditions.
• Bridging the Synthetic-to-Authentic Gap: Distortion-Guided Unsupervised Domain Adaptation for Blind Image Quality Assessment
  7 May 2024 1 repository listed
  The annotation of blind image quality assessment (BIQA) is labor-intensive and time-consuming, especially for authentic images.

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.