Papers › Cheating Depth: Enhancing 3D Surface Anomaly Detection via Depth Simulation
Cheating Depth: Enhancing 3D Surface Anomaly Detection via Depth Simulation
Vitjan Zavrtanik, Matej Kristan, Danijel Skočaj
RGB-based surface anomaly detection methods have advanced significantly. However, certain surface anomalies remain practically invisible in RGB alone, necessitating the incorporation of 3D information. Existing approaches that employ point-cloud backbones suffer from suboptimal representations and reduced applicability due to slow processing. Re-training RGB backbones, designed for faster dense input processing, on industrial depth datasets is hindered by the limited availability of sufficiently large datasets. We make several contributions to address these challenges. (i) We propose a novel Depth-Aware Discrete Autoencoder (DADA) architecture, that enables learning a general discrete latent space that jointly models RGB and 3D data for 3D surface anomaly detection. (ii) We tackle the lack of diverse industrial depth datasets by introducing a simulation process for learning informative depth features in the depth encoder. (iii) We propose a new surface anomaly detection method 3DSR, which outperforms all existing state-of-the-art on the challenging MVTec3D anomaly detection benchmark, both in terms of accuracy and processing speed. The experimental results validate the effectiveness and efficiency of our approach, highlighting the potential of utilizing depth information for improved surface anomaly detection.
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Depth Anomaly Detection and Segmentation | MVTEC 3D-AD | 3DSR (3D) | Detection AUROC | 0.922 | #6 of 13 | Archive leaderboard | report |
| Depth Anomaly Detection and Segmentation | MVTEC 3D-AD | 3DSR (3D) | Segmentation AUPRO | 0.907 | #6 of 13 | Archive leaderboard | report |
| RGB+3D Anomaly Detection and Segmentation | MVTEC 3D-AD | 3DSR | Detection AUCROC | 0.978 | #2 of 9 | Archive leaderboard | report |
| RGB+3D Anomaly Detection and Segmentation | MVTEC 3D-AD | 3DSR | Segmentation AUCROC | 0.995 | #2 of 9 | Archive leaderboard | report |
| RGB+3D Anomaly Detection and Segmentation | MVTEC 3D-AD | 3DSR | Segmentation AUPRO | 0.972 | #2 of 9 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
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