Data to 7 Oct 2026

Transformer for Image Quality Assessment

arXiv 2101.01097 ↗First posted 30 Dec 2020cs.CV cs.LG eess.IVcited by 76

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Abstract (arXiv)

Transformer has become the new standard method in natural language processing (NLP), and it also attracts research interests in computer vision area. In this paper we investigate the application of Transformer in Image Quality (TRIQ) assessment. Following the original Transformer encoder employed in Vision Transformer (ViT), we propose an architecture of using a shallow Transformer encoder on the top of a feature map extracted by convolution neural networks (CNN). Adaptive positional embedding is employed in the Transformer encoder to handle images with arbitrary resolutions. Different settings of Transformer architectures have been investigated on publicly available image quality databases. We have found that the proposed TRIQ architecture achieves outstanding performance. The implementation of TRIQ is published on Github (https://github.com/junyongyou/triq).

Key facts. Cited by 76 papers in the map (data through 7 Oct 2026). First posted on arXiv 30 Dec 2020.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 5; 2022: 15; 2023: 16; 2024: 21; 2025: 12; 2026: 7.

76 papers.

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2021MUSIQ: Multi-scale Image Quality Transformercited by 1,058
2022MANIQA: Multi-dimension Attention Network for No-Reference Image Quality Assessmentcited by 514
2023TOPIQ: A Top-down Approach from Semantics to Distortions for Image Quality Assessmentcited by 220
2021No-Reference Image Quality Assessment via Transformers, Relative Ranking, and Self-Consistencycited by 165
2022Attentions Help CNNs See Better: Attention-based Hybrid Image Quality Assessment Networkcited by 57
2021Perceptual Image Quality Assessment with Transformerscited by 54
2023Data-Efficient Image Quality Assessment with Attention-Panel Decodercited by 49
2024Large Multi-modality Model Assisted AI-Generated Image Quality Assessmentcited by 24
2024DSL-FIQA: Assessing Facial Image Quality via Dual-Set Degradation Learning and Landmark-Guided Transformercited by 17
2022A Perceptual Quality Metric for Video Frame Interpolationcited by 15
2023Quality-aware Pre-trained Models for Blind Image Quality Assessmentcited by 15
2024Video Quality Assessment: A Comprehensive Surveycited by 15

38 more

2022Content-Variant Reference Image Quality Assessment via Knowledge Distillationcited by 14
2022SwinIQA: Learned Swin Distance for Compressed Image Quality Assessmentcited by 14
2024DP-IQA: Utilizing Diffusion Prior for Blind Image Quality Assessment in the Wildcited by 14
2023An Image Quality Assessment Dataset for Portraitscited by 13
2024Quality Assessment for AI Generated Images with Instruction Tuningcited by 13
2024UniQA: Unified Vision-Language Pre-training for Image Quality and Aesthetic Assessmentcited by 12
2023Learning Generalizable Perceptual Representations for Data-Efficient No-Reference Image Quality Assessmentcited by 11
2025Next Token Is Enough: Realistic Image Quality and Aesthetic Scoring with Multimodal Large Language Modelcited by 11
2022A Quality Index Metric and Method for Online Self-Assessment of Autonomous Vehicles Sensory Perceptioncited by 10
2022MSTRIQ: No Reference Image Quality Assessment Based on Swin Transformer with Multi-Stage Fusioncited by 10
2022KonX: Cross-Resolution Image Quality Assessmentcited by 9
2023Transformer-based No-Reference Image Quality Assessment via Supervised Contrastive Learningcited by 9
2023Adaptive Feature Selection for No-Reference Image Quality Assessment by Mitigating Semantic Noise Sensitivitycited by 8
2021A survey on IQAcited by 6
2023ST360IQ: No-Reference Omnidirectional Image Quality Assessment with Spherical Vision Transformerscited by 6
2023Blind Image Quality Assessment via Transformer Predicted Error Map and Perceptual Quality Tokencited by 5
2024Feature Denoising Diffusion Model for Blind Image Quality Assessmentcited by 5
2024CrossScore: Towards Multi-View Image Evaluation and Scoringcited by 5
2024ATTIQA: Generalizable Image Quality Feature Extractor using Attribute-aware Pretrainingcited by 5
2024AI-Generated Image Quality Assessment Based on Task-Specific Prompt and Multi-Granularity Similaritycited by 5
2022Fine-grained Correlation Loss for Regressioncited by 4
2023Local Distortion Aware Efficient Transformer Adaptation for Image Quality Assessmentcited by 4
2023You Only Train Once: A Unified Framework for Both Full-Reference and No-Reference Image Quality Assessmentcited by 4
2022Dual Swin-Transformer based Mutual Interactive Network for RGB-D Salient Object Detectioncited by 3
2024Puzzle Similarity: A Perceptually-guided Cross-Reference Metric for Artifact Detection in 3D Scene Reconstructionscited by 3
2026MS-SCANet: A Multiscale Transformer-Based Architecture with Dual Attention for No-Reference Image Quality Assessmentcited by 3
2022Visual Mechanisms Inspired Efficient Transformers for Image and Video Quality Assessmentcited by 2
2022DCVQE: A Hierarchical Transformer for Video Quality Assessmentcited by 2
2023Regression-free Blind Image Quality Assessment with Content-Distortion Consistencycited by 2
2024Multi-Modal Prompt Learning on Blind Image Quality Assessmentcited by 2
2025Don't Judge Before You CLIP: A Unified Approach for Perceptual Taskscited by 2
2025Towards Explainable Partial-AIGC Image Quality Assessmentcited by 2
2025DGIQA: Depth-guided Feature Attention and Refinement for Generalizable Image Quality Assessmentcited by 2
2025Latent Guidance in Diffusion Models for Perceptual Evaluationscited by 2
2025MDIQA: Unified Image Quality Assessment for Multi-dimensional Evaluation and Restorationcited by 2
2026From Global to Granular: Revealing IQA Model Performance via Correlation Surfacecited by 2
2021Learning Transformer Features for Image Quality Assessmentcited by 1
2022Multi-Scale Features and Parallel Transformers Based Image Quality Assessmentcited by 1

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