Content for tag Anomaly Detection: Publications - 8 Introducing DIAD: A Novel Metric for Assessing the Difficulty of Anomaly Detection Problems Jure Pahor and Danijel Skočaj ERK 2025, 2025 Anomalous Sound Detection by Feature-Level Anomaly Simulation Vitjan Zavrtanik, Matija Marolt, Matej Kristan and Danijel Skočaj ICASSP 2024, 2024 Cheating Depth: Enhancing 3D Surface Anomaly Detection via Depth Simulation Vitjan Zavrtanik, Matej Kristan and Danijel Skočaj WACV 2024, 2024 Keep DRÆMing: Discriminative 3D anomaly detection through anomaly simulation Vitjan Zavrtanik, Matej Kristan and Danijel Skočaj Pattern Recognition Letters, 2024 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 Diskriminativna metoda za detekcijo 3D anomalij Vitjan Zavrtanik, Matej Kristan and Danijel Skočaj ERK, 2023 Multi-modal Obstacle Avoidance in USVs via Anomaly Detection and Cascaded Datasets Tilen Cvenkel, Marija Ivanovska, Jon Muhovič and Janez Perš International Conference on Advanced Concepts for Intelligent Vision Systems, Springer, 2023 DSR – A Dual Subspace Re-Projection Network for Surface Anomaly Detection Vitjan Zavrtanik, Matej Kristan and Danijel Skočaj ECCV 2022, 2022 Libraries - 6 3DSR Official implementation of 3DSR / 3DRÆM-style depth-simulation-based methods for 3D anomaly detection used in the WACV 2024, Pattern Recognition Letters 2024, and related MV4.0 outputs. AnomalyVFM Code for AnomalyVFM, a zero-shot anomaly detection framework based on vision foundation models. DSR Official implementation of DSR, a dual subspace re-projection network for surface anomaly detection from the ECCV 2022 paper. SALAD Code for SALAD, a semantics-aware logical anomaly detection method developed within MUXAD. 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.