Valeo Anomaly Dataset (VAD)

All images in VAD are captured from an actual production line, showcasing a diverse range of defects, from highly obvious to extremely subtle. This dataset bridges the gap between the academic community and the industry, offering researchers the chance to advance the performance of methods in tackling more intricate real-world challenges.

VAD consists of one class with predefined training and testing sets. The training set contains 1000 bad and 2000 good images, and the testing set contains 1000 bad, 165 of them are unseen defects, and 1000 good images. Unseen defects in the test dataset refer to several rare defect types that are not present in the training data.

More details are available at GitHub repository.