Comments (2)
@eric-tc because positional information allows to incorporate spatial prior to the model. For example, the model with such prior can learn how anomaly features should be arranged on the image.
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My experiments suggest that the model may have performed better without it (green using positional encoding)
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Related Issues (20)
- Detection AUROC and segmentation AUROC behavior HOT 1
- heatmap
- Custom datasets HOT 9
- Inference speed increase with the time HOT 1
- Calculate detection AUROC from anomaly map HOT 1
- Error when use resnet50 as feature extractor HOT 3
- Tune parameters to get best results. HOT 2
- About the difficulties of exporting onnx HOT 10
- U-L2? HOT 1
- Same model to inspect different but similar objects.
- Huge Training Loss after a certain number of epochs HOT 1
- What is the B value here in extracting feature map HOT 2
- Did the encoder training parameters setting in the paper refer to the pretrain parameters setting of the encoder? HOT 2
- Did the encoder training parameters setting in the paper refer to the pretrain parameters setting of the encoder?
- value of N
- test loss HOT 1
- The motivation and mechanism of conditional flow
- NameError: name 'mobilenet_v3_large' is not defined
- How to check visulization ?
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