Content for tag Surface Defect Detection:

Publications - 6

No Label Left Behind: A Unified Surface Defect Detection Model for all Supervision Regimes

Blaž Rolih, Matic Fučka and Danijel Skočaj

Journal of Intelligent Manufacturing, 2025
SuperSimpleNet: Unifying Unsupervised and Supervised Learning for Fast and Reliable Surface Defect Detection

Blaž Rolih, Matic Fučka and Danijel Skočaj

Pattern Recognition: 27th International Conference, ICPR 2024, Springer, 2024
Mixed supervision for surface-defect detection: from weakly to fully supervised learning

Jakob Božič, Domen Tabernik and Danijel Skočaj

Computers in Industry, Elsevier, 2021
End-to-end training of a two-stage neural network for defect detection

Jakob Božič, Domen Tabernik and Danijel Skočaj

ICPR, 2020
Segmentation-Based Deep-Learning Approach for Surface-Defect Detection

Domen Tabernik, Samo Šela, Jure Skvarč and Danijel Skočaj

Journal of Intelligent Manufacturing, 2020
Deep-learning-based computer vision system for surface-defect detection

Domen Tabernik, Samo Šela, Jure Skvarč and Danijel Skočaj

Proceedings of the 12th International Conference on Computer Vision Systems, 2019

Libraries - 3

DSR

Official implementation of DSR, a dual subspace re-projection network for surface anomaly detection from the ECCV 2022 paper.

SuperSimpleNet

PyTorch implementation of SuperSimpleNet for fast and reliable surface defect detection across unsupervised and supervised settings.

TransFusion

Official PyTorch implementation of TransFusion, a transparency-based diffusion model for anomaly detection from the ECCV 2024 paper.