HUST-SLOW / MuScLinks
[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.
☆14Updated last year
Alternatives and similar repositories for MuSc
Users that are interested in MuSc are comparing it to the libraries listed below
Sorting:
- [ICCV2025] SeaS: Few-shot Industrial Anomaly Image Generation with Separation and Sharing Fine-tuning. Paper is available at https://arxi…☆125Updated 6 months ago
- [CVPR2025] AnomalyNCD: Towards Novel Anomaly Class Discovery in Industrial Scenarios. Paper is available at https://arxiv.org/abs/2410.14…☆145Updated 5 months ago
- [IEEE TII 2023] Collaborative Discrepancy Optimization for Reliable Image Anomaly Localization☆81Updated 11 months ago
- Official implementation of the ECCV 2024 paper: TransFusion -- A Transparency-Based Diffusion Model for Anomaly Detection☆45Updated 9 months ago
- REB:Reducing Biases in Representation for Industrial Anomaly Detection☆26Updated 2 years ago
- CLIP-AD is an upgraded version of the zero-shot anomaly detection method we proposed for the VAND challenge.☆41Updated last year
- AAAI-2025: The largest and first anomaly detection dataset dedicated to 3C product quality control☆56Updated 9 months ago
- (ECCV 2024) VCP-CLIP: A visual context prompting model for zero-shot anomaly segmentation☆102Updated 8 months ago
- This Repository contain the PyTorch implementation of the multi-class unsupervised anomaly detection method, accepted in CVPR2025: "Corre…☆57Updated 6 months ago
- [arXiv2025] MuSc-V2: Zero-Shot Multimodal Industrial Anomaly Classification and Segmentation with Mutual Scoring of Unlabeled Samples. Pa…☆24Updated 2 months ago
- ☆56Updated last year
- [ECCV 2024] Few-Shot Anomaly-Driven Generation for Anomaly Detection☆68Updated 4 months ago
- (CVPR2025) the code of "Bayesian Prompt Flow Learning for Zero-Shot Anomaly Detection"☆63Updated 7 months ago
- [AAAI-2024] Offical code for <Unsupervised Continual Anomaly Detection with Contrastively-learned Prompt>.☆112Updated last year
- [CVPR 2023] Pytorch Implementation for CVPR2023 paper: Explicit Boundary Guided Semi-Push-Pull Contrastive Learning for Supervised Anomal…☆91Updated last year
- official code for paper entitled "Component-aware anomaly detection framework for adjustable and logical industrial visual inspection"☆46Updated last month
- [CVPR 2025] UniVAD: A Training-free Unified Model for Few-shot Visual Anomaly Detection☆177Updated 3 months ago
- [NeurIPS 2024] MetaUAS: Universal Anomaly Segmentation with One-Prompt Meta-Learning☆83Updated 5 months ago
- The official code of "GLAD: Towards Better Reconstruction with Global and Local Adaptive Diffusion Models for Unsupervised Anomaly Detect…☆112Updated 8 months ago
- ☆61Updated 8 months ago
- [ECCV 2024] Learning to Detect Multi-class Anomalies with Just One Normal Image Prompt☆69Updated 2 weeks ago
- Official implementation of paper FiLo: Zero-Shot Anomaly Detection by Fine-Grained Description and High-Quality Localization (ACM MM 2024…☆81Updated last year
- Accurate reimplementation of WinCLIP (pytorch version)☆132Updated last year
- A method for detecting anomalies consisting of unusual combinations of normal elements using set features☆36Updated last year
- Multi-Sensor Object Anomaly Detection: Unifying Appearance, Geometry, and Internal Properties(CVPR'25)☆80Updated 10 months ago
- ☆37Updated last year
- [NeurIPS 2024 Spotlight] Pytorch Implementation for NeurIPS 2024 paper: ResAD: A Simple Framework for Class Generalizable Anomaly Detecti…☆83Updated 3 months ago
- Official implementation of CVPR'24 paper 'Toward Generalist Anomaly Detection via In-context Residual Learning with Few-shot Sample Promp…☆202Updated 6 months ago
- Official implementation of DiAD: A Diffusion-based Framework for Multi-class Anomaly Detection.☆205Updated last year
- [TCSVT 2024] Official Implementation for "Progressive Boundary Guided Anomaly Synthesis for Industrial Anomaly Detection"☆33Updated 6 months ago