mlsanityData to 14 Oct 2026

Viewport-Unaware Blind Omnidirectional Image Quality Assessment: A Unified and Generalized Approach

arXiv 2604.23953 ↗First posted 27 Apr 2026cs.CV cs.AIcited by 0

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Abstract (arXiv)

Blind omnidirectional image quality assessment (BOIQA) presents a great challenge to the visual quality assessment community, due to different storage formats and diverse user viewing behaviors. The main paradigm of BOIQA models includes two steps, ie, viewport generation, and quality prediction, which brings an extra computational burden and is hard to generalize to other visual contents (eg, 2D planar image). Thus, in this paper, we make an attempt to solve these issues. First, we experimentally find that BOIQA can be formulated as a blind (2D planar) image quality assessment (BIQA) problem, ie, the first step - viewport generation - is no longer needed, which narrows the natural gap between BOIQA and BIQA. Then, we present a new BOIQA approach, which has three merits: ie, viewport-unaware - it accepts an omnidirectional image in the widely used equirectangular projection format as input without any transformation; unified - it can also be applied to BIQA; and generalized - it shows better generalizability against other competitors. Finally, we validate its promise by held-out test, cross-database validation, and the well-established gMAD competition.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 23 of its 60 references that are in the map. First posted on arXiv 27 Apr 2026.

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References · 23

  1. 2015Deep Residual Learning for Image Recognitioncited by 52,096
  2. 2017MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applicationscited by 3,845
  3. 2021Swin Transformer V2: Scaling Up Capacity and Resolutioncited by 1,228
  4. 2021MUSIQ: Multi-scale Image Quality Transformercited by 1,081
  5. 2018Deformable ConvNets v2: More Deformable, Better Resultscited by 670
  6. 2019KonIQ-10k: An ecologically valid database for deep learning of blind image quality assessmentcited by 355
  7. 2019Blind Image Quality Assessment Using A Deep Bilinear Convolutional Neural Networkcited by 302
  8. 2023Blind Image Quality Assessment via Vision-Language Correspondence: A Multitask Learning Perspectivecited by 280
  9. 2023TOPIQ: A Top-down Approach from Semantics to Distortions for Image Quality Assessmentcited by 226
  10. 2023Data-Efficient Image Quality Assessment with Attention-Panel Decodercited by 49
  11. 2025Toward Generalized Image Quality Assessment: Relaxing the Perfect Reference Quality Assumptioncited by 35
  12. 2022Perceptual Quality Assessment of Omnidirectional Imagescited by 34
11 more
  1. 2024Quality-Aware Image-Text Alignment for Opinion-Unaware Image Quality Assessmentcited by 32
  2. 2020Blind Omnidirectional Image Quality Assessment with Viewport Oriented Graph Convolutional Networkscited by 31
  3. 2023Assessor360: Multi-sequence Network for Blind Omnidirectional Image Quality Assessmentcited by 17
  4. 2024AIGCOIQA2024: Perceptual Quality Assessment of AI Generated Omnidirectional Imagescited by 16
  5. 2021Spatial Attention-based Non-reference Perceptual Quality Prediction Network for Omnidirectional Imagescited by 12
  6. 2025Subjective and Objective Quality Assessment of Non-Uniformly Distorted Omnidirectional Imagescited by 5
  7. 2025Omnidirectional Image Quality Captioning: A Large-scale Database and A New Modelcited by 5
  8. 2025Multitask Auxiliary Network for Perceptual Quality Assessment of Non-Uniformly Distorted Omnidirectional Imagescited by 3
  9. 2025Max360IQ: Blind Omnidirectional Image Quality Assessment with Multi-axis Attentioncited by 2
  10. 2025Viewport-Unaware Blind Omnidirectional Image Quality Assessment: A Flexible and Effective Paradigmcited by 2
  11. 2025Computational Analysis of Degradation Modeling in Blind Panoramic Image Quality Assessmentcited by 1

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