Closed PHaiJun closed 8 months ago
@DonaldRR
The FREEZING backbone is one of the key in this work. The pretrained backbone models the "normal" features distribution. When it's parameters are changing over time, such distribution will be changing too.
The essence of the training is not always Decreasing the Loss. The freezing backbone makes the features from backbone are meaningful,
@DonaldRR
excuse me, how could you get the good performence by this resposiry
why??
INFO:main:instance_auroc: 0.682 INFO:main:full_pixel_auroc: 0.661 INFO:main:anomaly_pixel_auroc: 0.007 INFO:main:
INFO:utils:instance_auroc: 0.682 INFO:utils:full_pixel_auroc: 0.661 INFO:utils:anomaly_pixel_auroc: 0.007