Video Quality Assessment on YouTube-UGC (10 train-test splits)
0.89SROCCDOVER
Evaluation Results
| Method | Links | ||
|---|---|---|---|
| DOVERSource (Pre-training) Quality Dataset=LSVQ [1], Fine-tuning=true2022.11 | 0.89 | 0.891 | |
| FAST-VQASource (Pre-training) Quality Dataset=LSVQ [1], Fine-tuning=true2022.11 | 0.855 | 0.852 | |
| Li et al.Source (Pre-training) Quality Dataset=fused ([15,73-75]), Fine-tuning=true2022.11 | 0.818 | 0.826 | |
| COINVQSource (Pre-training) Quality Dataset=self-collected, Fine-tuning=true2022.11 | 0.816 | 0.802 | |
| CNN-TLVQMSource (Pre-training) Quality Dataset=handcraft + KoNiQ [73], Fine-tuning=true2022.11 | 0.809 | 0.802 | |
| CNN-VIDEVALSource (Pre-training) Quality Dataset=handcraft + KoNiQ [73], Fine-tuning=true2022.11 | 0.808 | 0.803 | |
| VIDEVALSource (Pre-training) Quality Dataset=NA (pure handcraft), Fine-tuning=true2022.11 | 0.779 | 0.773 | |
| RAPIQUESource (Pre-training) Quality Dataset=handcraft + KoNiQ [73], Fine-tuning=true2022.11 | 0.759 | 0.768 | |
| VSFASource (Pre-training) Quality Dataset=None, Fine-tuning=true2022.11 | 0.724 | 0.743 | |
| TLVQMSource (Pre-training) Quality Dataset=NA (pure handcraft), Fine-tuning=true2022.11 | 0.669 | 0.659 |