tientrandinh Revisiting-Reverse-Distillation issues - Githubissues

tientrandinh / Revisiting-Reverse-Distillation

(CVPR 2023) Revisiting Reverse Distillation for Anomaly Detection

MIT License

113 stars 24 forks source link

issues

Newest

Newest Most commented Recently updated Oldest Least commented Least recently updated

I am using windows, where should my data set go? Thanks for your answer

#19 zhaozzt opened 2 weeks ago
0
running so slow

#18 sevenactors opened 2 months ago
1
Visualising the results

#17 neo133 opened 3 months ago
0
Trying on MVtec 3D dataset

#16 jcjlin opened 4 months ago
0
Error on The Colab Example

#15 Leminhhuy2386 opened 4 months ago
1
why do you have multiple models?

#14 Leminhhuy2386 closed 4 months ago
1
缺陷检测交流微信群，互相交流学习进步

#13 RuojiWang closed 3 months ago
16
Is it something wrong with grad acc?

#12 ArlixLin closed 7 months ago
1
May I ask if there are any good optimization methods for models that often detect normal samples as anomalies

#11 CvBokchoy opened 8 months ago
0
About the experimental results

#10 BensonZhanhg opened 9 months ago
0
Update resnet.py

#9 tdh512194 closed 9 months ago
0
where is GLEAM in resnet.py

#8 frankczh-123 closed 9 months ago
1
Is there C++ inference code?

#7 RaidenCJ closed 9 months ago
1
How to train my custom dataset?

#6 Ace-blue opened 1 year ago
3
When designing the loss_contrast，do we need to consider noise mask location information?

#5 hitlei closed 10 months ago
2
Clean imports

#4 tdh512194 closed 1 year ago
0
Clean imports

#3 tdh512194 closed 1 year ago
0
Add requirements file

#2 tdh512194 closed 1 year ago
0
Why the target in loss_contrast is 1?

#1 hitlei closed 1 year ago
1