Visual Anomaly (VisA)
amazon.science anomaly detection classification fewshot industrial segmentation
Description
Largest Visual Anomaly detection dataset containing objects from 12 classes in 3 domains across 10,821(9,621 normal and 1,200 anomaly) images. Both image and pixel level annotations are provided.
Update Frequency
Not updated
License
https://creativecommons.org/licenses/by/4.0/
Documentation
https://github.com/amazon-research/spot-diff
Managed By
See all datasets managed by Amazon Web Services.
Contact
Post any questions to re:Post and use the AWS Open Data tag.
How to Cite
Visual Anomaly (VisA) was accessed on DATE from https://registry.opendata.aws/visa. Zou, Yang, Jongheon Jeong, Latha Pemula, Dongqing Zhang, and Onkar Dabeer. "SPot-the-Difference Self-Supervised Pre-training for Anomaly Detection and Segmentation." arXiv preprint arXiv:2207.14315 (2022).
Usage Examples
Publications
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SPot-the-Difference Self-Supervised Pre-training for Anomaly Detection and Segmentation by Yang Zou, Jongheon Jeong, Latha Pemula, Dongqing Zhang, and Onkar Dabeer
Resources on AWS
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- Description
- The .tar file for the Visual Anomaly (VisA) dataset
- Resource type
- S3 Bucket
- Amazon Resource Name (ARN)
arn:aws:s3:::amazon-visual-anomaly/VisA_20220922.tar- AWS Region
us-west-2- AWS CLI Access (No AWS account required)
aws s3 ls --no-sign-request s3://amazon-visual-anomaly/VisA_20220922.tar/