mlsanityData to 7 Oct 2026

AIM 2024 Challenge on UHD Blind Photo Quality Assessment

arXiv 2409.16271 ↗First posted 24 Sep 2024cs.CVcited by 5

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Abstract (arXiv)

We introduce the AIM 2024 UHD-IQA Challenge, a competition to advance the No-Reference Image Quality Assessment (NR-IQA) task for modern, high-resolution photos. The challenge is based on the recently released UHD-IQA Benchmark Database, which comprises 6,073 UHD-1 (4K) images annotated with perceptual quality ratings from expert raters. Unlike previous NR-IQA datasets, UHD-IQA focuses on highly aesthetic photos of superior technical quality, reflecting the ever-increasing standards of digital photography. This challenge aims to develop efficient and effective NR-IQA models. Participants are tasked with creating novel architectures and training strategies to achieve high predictive performance on UHD-1 images within a computational budget of 50G MACs. This enables model deployment on edge devices and scalable processing of extensive image collections. Winners are determined based on a combination of performance metrics, including correlation measures (SRCC, PLCC, KRCC), absolute error metrics (MAE, RMSE), and computational efficiency (G MACs). To excel in this challenge, participants leverage techniques like knowledge distillation, low-precision inference, and multi-scale training. 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. The innovative solutions emerging from this competition will have implications for various applications, from photo curation and enhancement to image compression.

Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 32 of its 44 references that are in the map. First posted on arXiv 24 Sep 2024.

Builds on

32 of 44 references.

References · 32

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20 more
  1. 2023TOPIQ: A Top-down Approach from Semantics to Distortions for Image Quality Assessmentcited by 220
  2. 2022FAST-VQA: Efficient End-to-end Video Quality Assessment with Fragment Samplingcited by 179
  3. 2023Re-IQA: Unsupervised Learning for Image Quality Assessment in the Wildcited by 97
  4. 2021Image Quality Assessment using Contrastive Learningcited by 95
  5. 2023ARNIQA: Learning Distortion Manifold for Image Quality Assessmentcited by 87
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  13. 2022KonX: Cross-Resolution Image Quality Assessmentcited by 9
  14. 2024Assessing UHD Image Quality from Aesthetics, Distortions, and Saliencycited by 9
  15. 2024AIM 2024 Challenge on Compressed Video Quality Assessment: Methods and Resultscited by 7
  16. 2024AIM 2024 Challenge on Video Saliency Prediction: Methods and Resultscited by 7
  17. 2024AIM 2024 Sparse Neural Rendering Challenge: Dataset and Benchmarkcited by 6
  18. 2024ATTIQA: Generalizable Image Quality Feature Extractor using Attribute-aware Pretrainingcited by 5
  19. 2024AIM 2024 Sparse Neural Rendering Challenge: Methods and Resultscited by 4
  20. 2024MobileIQA: Exploiting Mobile-level Diverse Opinion Network For No-Reference Image Quality Assessment Using Knowledge Distillationcited by 1

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 2; 2025: 0; 2026: 3.

5 papers.