SimonThomine / RememberingNormalityLinks
Unofficial implementation of "Remembering Normality: Memory-guided Knowledge Distillation for Unsupervised Anomaly Detection"
☆20Updated 5 months ago
Alternatives and similar repositories for RememberingNormality
Users that are interested in RememberingNormality are comparing it to the libraries listed below
Sorting:
- [ECCV 2024] Learning to Detect Multi-class Anomalies with Just One Normal Image Prompt☆62Updated last month
- [CVPR2025] AnomalyNCD: Towards Novel Anomaly Class Discovery in Industrial Scenarios. Paper is available at https://arxiv.org/abs/2410.14…☆125Updated 3 months ago
- [AAAI-2024] Offical code for <Unsupervised Continual Anomaly Detection with Contrastively-learned Prompt>.☆111Updated last year
- The official code for "MSFlow: Multi-Scale Normalizing Flows for Unsupervised Anomaly Detection"☆80Updated last year
- ☆34Updated last year
- ☆59Updated 7 months ago
- [CVPR 2023] Pytorch Implementation for CVPR2023 paper: Explicit Boundary Guided Semi-Push-Pull Contrastive Learning for Supervised Anomal…☆90Updated last year
- [NeurIPS2023] Official Implementation of "ReContrast: Domain-Specific Anomaly Detection via Contrastive Reconstruction".☆47Updated last year
- Official implementation of CVPR'24 paper 'Anomaly Heterogeneity Learning for Open-set Supervised Anomaly Detection'.☆52Updated last year
- ☆30Updated 2 years ago
- MoEAD is a parameter efficient model for multi class anomaly detection☆33Updated 11 months ago
- [IEEE TII 2023] Collaborative Discrepancy Optimization for Reliable Image Anomaly Localization☆80Updated 9 months ago
- [ICCV2025] SeaS: Few-shot Industrial Anomaly Image Generation with Separation and Sharing Fine-tuning. Paper is available at https://arxi…☆106Updated 4 months ago
- official code for paper entitled "Component-aware anomaly detection framework for adjustable and logical industrial visual inspection"☆47Updated 5 months ago
- [CVPR 2023] Unofficial PyTorch implementation for CVPR2023 paper, Prototypical Residual Networks for Anomaly Detection and Localization.☆35Updated 2 years ago
- [NeurIPS 2024] Official implementation of MambaAD: Exploring State Space Models for Multi-class Unsupervised Anomaly Detection.☆188Updated 8 months ago
- REB:Reducing Biases in Representation for Industrial Anomaly Detection☆26Updated last year
- ☆89Updated 2 years ago
- This is official implementation of Multi-scale feature reconstruction network for industrial anomaly detection☆18Updated 5 months ago
- A method for detecting anomalies consisting of unusual combinations of normal elements using set features☆36Updated last year
- ☆13Updated last year
- Code for NeurIPS 2022 paper "SoftKernel: Unsupervised Anomaly Detection with Noisy Data"☆80Updated last year
- CLIP-AD is an upgraded version of the zero-shot anomaly detection method we proposed for the VAND challenge.☆40Updated last year
- (ECCV 2024) VCP-CLIP: A visual context prompting model for zero-shot anomaly segmentation☆101Updated 6 months ago
- This Repository contain the PyTorch implementation of the multi-class unsupervised anomaly detection method, accepted in CVPR2025: "Corre…☆51Updated 4 months ago
- GeneralAD☆56Updated 11 months ago
- [ECCV 2024] Learning Unified Reference Representation for Unsupervised Multi-class Anomaly Detection☆17Updated last year
- ☆56Updated last year
- [NeurIPS 2024 Spotlight] Pytorch Implementation for NeurIPS 2024 paper: ResAD: A Simple Framework for Class Generalizable Anomaly Detecti…☆82Updated last month
- [TCSVT 2024] Official Implementation for "Progressive Boundary Guided Anomaly Synthesis for Industrial Anomaly Detection"☆32Updated 4 months ago