| Unified Quality Assessment of In-the-Wild Videos with Mixed Datasets Training | ✓ Link | 0.9289 | 0.9431 | 0.7883 | NR | MDTVSFA | 2020-11-09 |
| Blind Image Quality Assessment Using A Deep Bilinear Convolutional Neural Network | ✓ Link | 0.9220 | 0.9222 | 0.7750 | NR | DBCNN | 2019-07-05 |
| UNIQUE: Unsupervised Image Quality Estimation | ✓ Link | 0.9148 | 0.9238 | 0.7648 | NR | UNIQUE | 2018-10-15 |
| Blindly Assess Quality of In-the-Wild Videos via Quality-aware Pre-training and Motion Perception | ✓ Link | 0.9131 | 0.9270 | 0.7640 | NR | LI | 2021-08-19 |
| Norm-in-Norm Loss with Faster Convergence and Better Performance for Image Quality Assessment | ✓ Link | 0.9104 | 0.9106 | 0.7589 | NR | LINEARITY | 2020-08-10 |
| Quality Assessment of In-the-Wild Videos | ✓ Link | 0.9049 | 0.9180 | 0.7483 | NR | VSFA | 2019-08-01 |
| MUSIQ: Multi-scale Image Quality Transformer | ✓ Link | 0.9004 | 0.9068 | 0.7433 | NR | MUSIQ | 2021-08-12 |
| Exploring Video Quality Assessment on User Generated Contents from Aesthetic and Technical Perspectives | ✓ Link | 0.8871 | 0.9099 | 0.7216 | NR | DOVER | 2022-11-09 |
| Perceptual Quality Assessment of Smartphone Photography | ✓ Link | 0.8822 | 0.8814 | 0.7186 | NR | SPAQ MT-S | 2020-06-01 |
| Perceptual Quality Assessment of Smartphone Photography | ✓ Link | 0.8799 | 0.8855 | 0.7106 | NR | SPAQ BL | 2020-06-01 |
| Perceptual Quality Assessment of Smartphone Photography | ✓ Link | 0.8794 | 0.8824 | 0.7148 | NR | SPAQ MT-A | 2020-06-01 |
| Deep Learning based Full-reference and No-reference Quality Assessment Models for Compressed UGC Videos | ✓ Link | 0.8742 | 0.8933 | 0.7037 | NR | GVSP-UGCVQA-NR (single_scale) | 2021-06-02 |
| From Patches to Pictures (PaQ-2-PiQ): Mapping the Perceptual Space of Picture Quality | ✓ Link | 0.8705 | 0.8549 | 0.7079 | NR | PaQ-2-PiQ | 2019-12-20 |
| Deep Learning based Full-reference and No-reference Quality Assessment Models for Compressed UGC Videos | ✓ Link | 0.8673 | 0.8851 | 0.6942 | NR | GVSP-UGCVQA-NR (multi_scale) | 2021-06-02 |
| NIMA: Neural Image Assessment | ✓ Link | 0.8494 | 0.8784 | 0.6745 | NR | NIMA | 2017-09-15 |
| KonIQ-10k: An ecologically valid database for deep learning of blind image quality assessment | ✓ Link | 0.8360 | 0.8464 | 0.6608 | NR | KonCept512 | 2019-10-14 |
| FAST-VQA: Efficient End-to-end Video Quality Assessment with Fragment Sampling | ✓ Link | 0.8308 | 0.8613 | 0.6498 | NR | FAST-VQA | 2022-07-06 |
| FAST-VQA: Efficient End-to-end Video Quality Assessment with Fragment Sampling | ✓ Link | 0.7508 | 0.8087 | 0.5645 | NR | FASTER-VQA | 2022-07-06 |
| UGC-VQA: Benchmarking Blind Video Quality Assessment for User Generated Content | ✓ Link | 0.7286 | 0.7717 | 0.5414 | NR | VIDEVAL | 2020-05-29 |
| Barriers towards no-reference metrics application to compressed video quality analysis: on the example of no-reference metric NIQE | | 0.5985 | 0.6713 | 0.4215 | NR | Y-NIQE | 2019-07-08 |
| []() | | 0.5066 | 0.2898 | 0.3775 | NR | MEON | |