Comments (1)
Hi @Howeng98 in this paper, I didn't really prioritize detection performance. That's why I simply take max of 2D anomaly map. More advanced aggregation methods should perform better like in other flow-based papers.
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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
- 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?
- Why use positional embedding as conditional vector? HOT 2
- 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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