huangjk97 / T2T

Code for the paper: "Trash to Treasure: Harvesting OOD Data with Cross-Modal Matching for Open-Set Semi-Supervised Learning"
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Question regarding Table 4 results #4

Open YUE-FAN opened 1 year ago

YUE-FAN commented 1 year ago

Dear Authors,

I have a question regarding the results in Table 4 in your paper. T2T gives 99.85% AUROC on CIFAR-ID-50 with TIN. However, this setting does not have a hold-out test set for OOD classes because you use the test set of TIN for training. So on which test set do you compute the result 99.85%?

Using your code, I can only reproduce this number if evaluating the model on the training set (CIFAR-ID-50 unlabeled set + TIN). So my understanding is this number is training AUROC and should not be compared with other numbers.

buzhiqimeiliuqiangdong commented 1 year ago

Dear Authors,

I have a question regarding the results in Table 4 in your paper. T2T gives 99.85% AUROC on CIFAR-ID-50 with TIN. However, this setting does not have a hold-out test set for OOD classes because you use the test set of TIN for training. So on which test set do you compute the result 99.85%?

Using your code, I can only reproduce this number if evaluating the model on the training set (CIFAR-ID-50 unlabeled set + TIN). So my understanding is this number is training AUROC and should not be compared with other numbers.

兄你有这篇论文里测试AUROC的代码吗,作者的代码里好像没给