ShuaiLYU / MVTec-FS
The MVTec-FS dataset is a refined version of the MVTec AD dataset, designed for few-shot learning research.
☆11Updated 4 months ago
Alternatives and similar repositories for MVTec-FS
Users that are interested in MVTec-FS are comparing it to the libraries listed below
Sorting:
- Official source code for MVREC: A General Few-shot Defect Classification Model Using Multi-View Region-Context.(AAAI 2025)☆18Updated 4 months ago
- [CVPR2025] AnomalyNCD: Towards Novel Anomaly Class Discovery in Industrial Scenarios. Paper is available at https://arxiv.org/abs/2410.14…☆51Updated last month
- ☆28Updated 10 months ago
- ☆49Updated 10 months ago
- ☆30Updated 3 months ago
- [AAAI 2025] PyTorch Implementation of "Unlocking the Potential of Reverse Distillation for Anomaly Detection".☆19Updated 2 months ago
- [CVPR 2025] UniVAD: A Training-free Unified Model for Few-shot Visual Anomaly Detection☆51Updated last month
- Official implementation of the ECCV 2024 paper: TransFusion -- A Transparency-Based Diffusion Model for Anomaly Detection☆37Updated last month
- [ECCV 2024] Few-Shot Anomaly-Driven Generation for Anomaly Detection☆36Updated 6 months ago
- AAAI-2025: The largest and first anomaly detection dataset dedicated to 3C product quality control☆39Updated 2 weeks ago
- The official implementation of AA-CLIP: Enhancing Zero-shot Anomaly Detection via Anomaly-Aware CLIP☆54Updated last week
- ☆108Updated last month
- Official implementation of paper FiLo: Zero-Shot Anomaly Detection by Fine-Grained Description and High-Quality Localization (ACM MM 2024…☆64Updated 9 months ago
- [CVPR 2025] official implementation of “Exploring Intrinsic Normal Prototypes within a Single Image for Universal Anomaly Detection”☆101Updated 3 weeks ago
- [NeurIPS 2024 Spotlight] Pytorch Implementation for NeurIPS 2024 paper: ResAD: A Simple Framework for Class Generalizable Anomaly Detecti…☆60Updated 6 months ago
- (ECCV 2024) VCP-CLIP: A visual context prompting model for zero-shot anomaly segmentation☆79Updated 6 months ago
- CLIP-AD is an upgraded version of the zero-shot anomaly detection method we proposed for the VAND challenge.☆37Updated last year
- [CVPR 2025] The official implementation of “UniNet: A Contrastive Learning-guided Unified Framework with Feature Selection for Anomaly De…☆32Updated this week
- The official code of "GLAD: Towards Better Reconstruction with Global and Local Adaptive Diffusion Models for Unsupervised Anomaly Detect…☆84Updated last month
- ☆14Updated 10 months ago
- [AAAI-2024] Offical code for <Unsupervised Continual Anomaly Detection with Contrastively-learned Prompt>.☆97Updated 9 months ago
- [ICLR2024] MuSc : Zero-Shot Industrial Anomaly Classification and Segmentation with Mutual Scoring of the Unlabeled Images (The original …☆11Updated 11 months ago
- [ICPR 2024] Official implementation of SuperSimpleNet: Unifying Unsupervised and Supervised Learning for Fast and Reliable Surface Defect…☆57Updated 3 weeks ago
- The official implementation of “One-for-More: Continual Diffusion Model for Anomaly Detection” (CVPR2025)☆19Updated this week
- [ICCV2023] Unsupervised Surface Anomaly Detection with Diffusion Probabilistic Model☆26Updated last year
- [ECCV2024] The Official Implementation for ''AdaCLIP: Adapting CLIP with Hybrid Learnable Prompts for Zero-Shot Anomaly Detection''☆215Updated 4 months ago
- REB:Reducing Biases in Representation for Industrial Anomaly Detection☆25Updated last year
- Official implement of ICLR 2025 "One-for-All Few-Shot Anomaly Detection via Instance-Induced Prompt Learning"☆13Updated this week
- GeneralAD☆53Updated 4 months ago
- ☆20Updated 4 months ago