Exposing Outlier Exposure: What Can Be Learned From Few, One, and Zero Outlier Images | ✓ Link | 99.6 | CLIP (OE) | 2022-05-23 |
GeneralAD: Anomaly Detection Across Domains by Attending to Distorted Features | ✓ Link | 99.3 | GeneralAD | 2024-07-17 |
Fake It Till You Make It: Towards Accurate Near-Distribution Novelty Detection | ✓ Link | 99.1 | Fake It Till You Make It | 2022-05-28 |
When Text and Images Don't Mix: Bias-Correcting Language-Image Similarity Scores for Anomaly Detection | | 99.1 | BLISS | 2024-07-24 |
PANDA: Adapting Pretrained Features for Anomaly Detection and Segmentation | ✓ Link | 98.9 | PANDA-OE | 2020-10-12 |
Mean-Shifted Contrastive Loss for Anomaly Detection | ✓ Link | 98.6 | Mean-Shifted Contrastive Loss | 2021-06-07 |
Exposing Outlier Exposure: What Can Be Learned From Few, One, and Zero Outlier Images | ✓ Link | 98.5 | CLIP (zero shot) | 2022-05-23 |
Anomaly Detection Requires Better Representations | ✓ Link | 98.4 | DINO-FT | 2022-10-19 |
Transformaly -- Two (Feature Spaces) Are Better Than One | ✓ Link | 98.3 | Transformaly | 2021-12-08 |
Constrained Adaptive Projection with Pretrained Features for Anomaly Detection | ✓ Link | 97.0 | CAP | 2021-12-05 |
PANDA: Adapting Pretrained Features for Anomaly Detection and Segmentation | ✓ Link | 96.2 | PANDA | 2020-10-12 |
CSI: Novelty Detection via Contrastive Learning on Distributionally Shifted Instances | ✓ Link | 94.3 | CSI | 2020-07-16 |
Deep Unsupervised Image Anomaly Detection: An Information Theoretic Framework | | 92.6 | DUIAD | 2020-12-09 |
Deep Nearest Neighbor Anomaly Detection | | 92.5 | DN2 | 2020-02-24 |
Learning and Evaluating Representations for Deep One-class Classification | ✓ Link | 92.5 | DisAug CLR | 2020-11-04 |
Explainable Deep One-Class Classification | ✓ Link | 92 | FCDD | 2020-07-03 |
Deep One-Class Classification via Interpolated Gaussian Descriptor | ✓ Link | 91.25 | IGD (pre-trained SSL) | 2021-01-25 |
GAN-based Anomaly Detection in Imbalance Problems | | 90.6 | GAN based Anomaly Detection in Imbalance Problems | 2020-08-28 |
Using Self-Supervised Learning Can Improve Model Robustness and Uncertainty | ✓ Link | 90.1 | SSOOD | 2019-06-28 |
SSD: A Unified Framework for Self-Supervised Outlier Detection | ✓ Link | 90.0 | SSD | 2021-03-22 |
Unsupervised Two-Stage Anomaly Detection | | 88.4 | UTAD | 2021-03-22 |
Classification-Based Anomaly Detection for General Data | ✓ Link | 88.2 | GOAD | 2020-05-05 |
Attribute Restoration Framework for Anomaly Detection | ✓ Link | 86.6 | ARNET | 2019-11-25 |
Anomaly Detection via Reverse Distillation from One-Class Embedding | ✓ Link | 86.5 | Reverse Distillation | 2022-01-26 |
Deep Anomaly Detection Using Geometric Transformations | ✓ Link | 86 | ADT | 2018-05-28 |
Deep One-Class Classification via Interpolated Gaussian Descriptor | ✓ Link | 83.68 | IGD (pre-trained ImageNet) | 2021-01-25 |
ESAD: End-to-end Deep Semi-supervised Anomaly Detection | | 83.3 | ESAD | 2020-12-09 |
Deep One-Class Classification via Interpolated Gaussian Descriptor | ✓ Link | 74.33 | IGD (scratch) | 2021-01-25 |
P-KDGAN: Progressive Knowledge Distillation with GANs for One-class Novelty Detection | | 73.05 | P-KDGAN | 2020-07-14 |
OLED: One-Class Learned Encoder-Decoder Network with Adversarial Context Masking for Novelty Detection | ✓ Link | 67.1 | OLED | 2021-03-27 |
OCGAN: One-class Novelty Detection Using GANs with Constrained Latent Representations | | 66.83 | OCGAN | 2019-03-20 |
FastFlow: Unsupervised Anomaly Detection and Localization via 2D Normalizing Flows | ✓ Link | 66.7 | FastFlow | 2021-11-15 |
DASVDD: Deep Autoencoding Support Vector Data Descriptor for Anomaly Detection | ✓ Link | 66.5 | DASVDD | 2021-06-09 |
Deep One-Class Classification | ✓ Link | 65.7 | Deep SVDD | 2018-07-01 |
PANDA: Adapting Pretrained Features for Anomaly Detection and Segmentation | ✓ Link | 64.8 | Self-Supervised DeepSVDD | 2020-10-12 |
PANDA: Adapting Pretrained Features for Anomaly Detection and Segmentation | ✓ Link | 64.7 | Self-Supervised One-class SVM, RBF kernel | 2020-10-12 |