HUST-SLOW / MuSc
[ICLR2024] MuSc : Zero-Shot Industrial Anomaly Classification and Segmentation with Mutual Scoring of the Unlabeled Images (The original repo is available at https://github.com/xrli-U/MuSc)
☆9Updated 5 months ago
Related projects ⓘ
Alternatives and complementary repositories for MuSc
- [arXiv:2410.14379] AnomalyNCD: Towards Novel Anomaly Class Discovery in Industrial Scenarios. Paper is available at https://arxiv.org/abs…☆19Updated 5 months ago
- The official code of "GLAD: Towards Better Reconstruction with Global and Local Adaptive Diffusion Models for Unsupervised Anomaly Detect…☆49Updated 4 months ago
- ☆47Updated 4 months ago
- ☆51Updated 2 weeks ago
- [TII 2023] Collaborative Discrepancy Optimization for Reliable Image Anomaly Localization☆63Updated last year
- REB:Reducing Biases in Representation for Industrial Anomaly Detection☆20Updated 9 months ago
- ☆12Updated 4 months ago
- ☆11Updated 5 months ago
- Accurate reimplementation of WinCLIP (pytorch version)☆77Updated 3 months ago
- AnomalyDINO: Boosting Patch-based Few-shot Anomaly Detection with DINOv2☆24Updated last month
- Official implementation of DiAD: A Diffusion-based Framework for Multi-class Anomaly Detection.☆138Updated 6 months ago
- ☆15Updated 4 months ago
- Evaluation Tool for Anomaly Detection Research☆12Updated 6 months ago
- [AAAI-2024] Offical code for <Unsupervised Continual Anomaly Detection with Contrastively-learned Prompt>.☆74Updated 3 months ago
- [ICCV 2023] Pytorch Implementation for ICCV2023 paper: Focus the Discrepancy: Intra- and Inter-Correlation Learning for Image Anomaly Det…☆41Updated last week
- CLIP-AD is an upgraded version of the zero-shot anomaly detection method we proposed for the VAND challenge.☆21Updated 8 months ago
- [NeurIPS 2024] Official implementation of MambaAD: Exploring State Space Models for Multi-class Unsupervised Anomaly Detection.☆122Updated last month
- (ECCV 2024) VCP-CLIP: A visual context prompting model for zero-shot anomaly segmentation☆48Updated 3 weeks ago
- A method for detecting anomalies consisting of unusual combinations of normal elements using set features☆34Updated this week
- Official implementation of CVPR 2024 PromptAD: Learning Prompts with Only Normal Samples for Few-Shot Anomaly Detection☆97Updated 2 months ago
- [ICPR 2024] Official implementation of SuperSimpleNet: Unifying Unsupervised and Supervised Learning for Fast and Reliable Surface Defect…☆30Updated last month
- [ECCV 2024] Few-Shot Anomaly-Driven Generation for Anomaly Detection☆15Updated 2 weeks ago
- [CVPR 2023] PyramidFlow: High-Resolution Defect Contrastive Localization using Pyramid Normalizing Flow☆55Updated last year
- Official implementation of CVPR'24 paper 'Toward Generalist Anomaly Detection via In-context Residual Learning with Few-shot Sample Promp…☆127Updated 2 months ago
- Official implementation of paper FiLo: Zero-Shot Anomaly Detection by Fine-Grained Description and High-Quality Localization (ACM MM 2024…☆32Updated 3 months ago
- [ICCV2023] Unsupervised Surface Anomaly Detection with Diffusion Probabilistic Model☆16Updated 6 months ago
- [CVPR 2023] Pytorch Implementation for CVPR2023 paper: Explicit Boundary Guided Semi-Push-Pull Contrastive Learning for Supervised Anomal…☆78Updated last week
- official code for paper entitled "Component-aware anomaly detection framework for adjustable and logical industrial visual inspection"☆40Updated 6 months ago
- The implement for paper : "A Novel Approach to Industrial Defect Generation through Blended Latent Diffusion Model with Online Adaptation…☆56Updated 6 months ago
- [ECCV2024] The Official Implementation for ''AdaCLIP: Adapting CLIP with Hybrid Learnable Prompts for Zero-Shot Anomaly Detection''☆114Updated 2 months ago