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Training UNIQUE on single dataset #3
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@pencilzhang The main advantage of UNIQUE over traditional training strategies is it enables a BIQA model to be trained on multiple databases under a learning-to-rank framework. In our preliminary experiment, we tried training UNIQUE on a single dataset, yet we find that the proposed method brings no benefit to single-dataset training. It is a reasonable result since training by ranking alone does not introduce any extra information compared with training with regression. In our ablation study, we use regression to obtain the results because the training time is significantly lower than the learning-to-rank method. Note that we sample a large number of image pairs from a dataset. |
@zwx8981 Thanks for your quick reply!
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@pencilzhang |
Hi,
I have a question about Table VII in your recent arxiv paper.
I noticed that you did single-dataset training on baseline model (regression) to compare with UNIQIE model trained on multiple datasets, as shown in Table VII.
Why did not train UNIQUE model on one single dataset?
Thanks in advance!
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