Anomaly detection 분야 구현 및 논문 리뷰 할 것들

https://paperswithcode.com/sota/anomaly-detection-on-one-class-cifar-10

Papers with Code - One-class CIFAR-10 Benchmark (Anomaly Detection)

 

 

ITAE-Pytorch-Anomaly_Detection

https://github.com/yuxiao-ash/ITAE-Pytorch-Anomaly_Detection?tab=readme-ov-file

GitHub - yuxiao-ash/ITAE-Pytorch-Anomaly_Detection: An unofficial implementation of 'Inverse-Transform AutoEncoder for Anomaly D

 

 

SSD: A Unified Framework for Self-Supervised Outlier Detection [ICLR 2021]

https://github.com/inspire-group/SSD?tab=readme-ov-file

GitHub - inspire-group/SSD: SSD: A Unified Framework for Self-Supervised Outlier Detection [ICLR 2021]

 

Explainable Deep One-Class Classification

https://github.com/liznerski/fcdd/tree/windows?tab=readme-ov-file

GitHub - liznerski/fcdd: Repository for the Explainable Deep One-Class Classification paper

 

“PANDA: Adapting Pretrained Features for Anomaly Detection and Segmentation” (CVPR 2021).

https://github.com/talreiss/PANDA?tab=readme-ov-file

 

Constrained Adaptive Projection with Pretrained Features for Anomaly Detection(IJCAI 2022)

https://github.com/tabguigui/cap?tab=readme-ov-file

GitHub - TabGuigui/CAP: Implementation of "Constrained Adaptive Projection with Pretrained Features for Anomaly Detection"

 

Mean-Shifted Contrastive Loss for Anomaly Detection

https://github.com/talreiss/Mean-Shifted-Anomaly-Detection?tab=readme-ov-file

GitHub - talreiss/Mean-Shifted-Anomaly-Detection: Mean-Shifted Contrastive Loss for Anomaly Detection (AAAI 2023)