Contamination Map Methodology

Vision / Dataset

MVTec LOCO AD

3644 images from five categories (breakfast box, juice bottle, pushpins, screw bag, splicing connectors) with structural and logical anomalies: 1772 training, 304 validation and 1568 test images. Training and validation images are anomaly-free; the test set contains anomaly-free images and images with logical and structural anomalies, with pixel-precise ground truth for each anomalous region.

Also known as
MVTec logical constraints anomaly detection, MVTec LOCO, LOCO AD
Domain
manufacturing inspection
License
CC BY-NC-SA 4.0
Test items from
2022-02-22
Evidence
“Published: 22 February 2022”
link.springer.com · paper · article metadata · retrieved 2026-10-15
Homepage
www.mvtec.com

Exposure by model

BenchmarkModelLevelReason
Industrial anomaly detection AA-CLIP, trained on MVTec AD (for VisA results) Unknown unknown for its base model OpenAI CLIP: training data not disclosed in enough detail
Industrial anomaly detection AA-CLIP, trained on VisA Unknown unknown for its base model OpenAI CLIP: training data not disclosed in enough detail
Industrial anomaly detection AdaCLIP, trained on all 14 datasets (demo model) Unknown unknown for its base model OpenAI CLIP: training data not disclosed in enough detail
Industrial anomaly detection AdaCLIP, trained on MVTec AD + ColonDB Unknown unknown for its base model OpenAI CLIP: training data not disclosed in enough detail
Industrial anomaly detection AdaCLIP, trained on VisA + ClinicDB Unknown unknown for its base model OpenAI CLIP: training data not disclosed in enough detail
Industrial anomaly detection AdaptCLIP, trained on MVTec AD Unknown unknown for its base model OpenAI CLIP: training data not disclosed in enough detail
Industrial anomaly detection AdaptCLIP, trained on VisA Unknown unknown for its base model OpenAI CLIP: training data not disclosed in enough detail
Industrial anomaly detection Anomaly-OneVision (Anomaly-OV) Unknown unknown for its base model LLaVA-OneVision: unknown for its base model SigLIP: training data not disclosed in enough detail
Industrial anomaly detection AnomalyCLIP, trained on MVTec AD Unknown unknown for its base model OpenAI CLIP: training data not disclosed in enough detail
Industrial anomaly detection AnomalyCLIP, trained on VisA Unknown unknown for its base model OpenAI CLIP: training data not disclosed in enough detail
Industrial anomaly detection AnomalyDINO Unknown unknown for its base model DINOv2: training data not disclosed in enough detail
Industrial anomaly detection AnomalyGPT, unsupervised on MVTec AD Unknown training data not disclosed in enough detail
Industrial anomaly detection AnomalyGPT, supervised (demo model) Seen, split unclear in fine-tuning data: the dataset was used; the source does not say which part
Industrial anomaly detection AnomalyGPT, unsupervised on VisA Unknown training data not disclosed in enough detail
Industrial anomaly detection APRIL-GAN (VAND 2023), trained on MVTec AD Unknown unknown for its base model OpenAI CLIP: training data not disclosed in enough detail
Industrial anomaly detection APRIL-GAN (VAND 2023), trained on VisA Unknown unknown for its base model OpenAI CLIP: training data not disclosed in enough detail
Industrial anomaly detection OpenAI CLIP Unknown training data not disclosed in enough detail
Industrial anomaly detection DINOv2 Unknown training data not disclosed in enough detail
Industrial anomaly detection DINOv3 (web / LVD-1689M models) Unknown training data not disclosed in enough detail
Industrial anomaly detection FiLo, trained on MVTec AD Unknown unknown for its base model OpenAI CLIP: training data not disclosed in enough detail
Industrial anomaly detection FiLo, trained on VisA Unknown unknown for its base model OpenAI CLIP: training data not disclosed in enough detail
Industrial anomaly detection WideResNet-50-2 (supervised ImageNet-1k, torchvision) Not seen absent from the complete list of training data
Industrial anomaly detection InCTRL, trained on MVTec AD Not seen absent from the complete list of training data and from its base models' data
Industrial anomaly detection InCTRL, trained on VisA Not seen absent from the complete list of training data and from its base models' data
Industrial anomaly detection MetaUAS Unknown training data not disclosed in enough detail
Industrial anomaly detection MuSc Unknown unknown for its base model OpenAI CLIP: training data not disclosed in enough detail
Industrial anomaly detection OpenCLIP (LAION-2B checkpoints) Not seen its test items were published from 2022-02-22, after the model's stated training-data cutoff (2022-01-31)
Industrial anomaly detection OpenCLIP (LAION-400M checkpoints) Not seen its test items were published from 2022-02-22, after the model's stated training-data cutoff (2021-12-31)
Industrial anomaly detection Segment Any Anomaly (SAA / SAA+) Unknown unknown for its base model Segment Anything Model (SAM): training data not disclosed in enough detail
Industrial anomaly detection SAM 2 / SAM 2.1 Unknown training data not disclosed in enough detail
Industrial anomaly detection Segment Anything Model (SAM) Unknown training data not disclosed in enough detail
Industrial anomaly detection SigLIP 2 Unknown training data not disclosed in enough detail
Industrial anomaly detection SigLIP Unknown training data not disclosed in enough detail
Industrial anomaly detection UniVAD Unknown unknown for its base model OpenAI CLIP: training data not disclosed in enough detail
Industrial anomaly detection VCP-CLIP, trained on MVTec-AD Unknown unknown for its base model OpenAI CLIP: training data not disclosed in enough detail
Industrial anomaly detection VCP-CLIP, trained on VisA Unknown unknown for its base model OpenAI CLIP: training data not disclosed in enough detail
Industrial anomaly detection WinCLIP / WinCLIP+ Not seen absent from the complete list of training data and from its base models' data

Notes

published_from = IJCV online publication date (received 23 March 2021). Category names other than breakfast box, screw bag and pushpins were not quote-checked. Download requires filling in a form.

Sources