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ViCoS Lab

Matic Fučka, MSc

Researcher
  matic.fucka@fri.uni-lj.si

About

I am a PhD student at the Visual Cognitive Systems Lab at the University of Ljubljana, Faculty of Computer and Information Science. My research is supervised by prof. dr. Danijel Skočaj and focuses on the development of methods for detecting anomalies.

I have a diverse range of research interest, such as visual anomaly detection, image generation, zero-shot semantic segmentation, few-shot learning, and the broader domains of computer vision and deep learning.

I am engaged in both research and industry projects, where I apply computer vision and deep learning techniques to address real-world problems, applications, and diverse challenges.


Research

Visual anomaly detection

This research focuses on the development of unsupervised visual anomaly detection methods. Trained on anomaly-free samples only, these methods attempt to remove the need for a difficult acquisition of a diverse set of anomalous objects while aiming to match the performance of supervised methods.

Projects

MUXADMultimodal Image Understanding for Explainable Anomaly Detection

January 2025 - December 2027
The functional objective of the project is to advance anomaly detection in images by developing multimodal models that integrate visual and linguistic information to not only detect if and where anomalies occur but also explain why. The main research goal is to create novel methods for semantic image understanding, zero-shot multimodal anomaly detection, and multimodal explanations that improve AI’s interpretability and transparency while reducing reliance on annotated data.

MV4.0Data-driven framework for development of machine vision solutions

October 2021 - September 2025
MV4.0 developed a data-driven framework for industrial machine vision that reduces reliance on large densely annotated datasets by combining synthetic data generation, annotation-efficient learning, and self-supervised / unsupervised visual modelling. The project concluded with validated methods for surface-defect detection, object localization and 3DoF pose-related perception, public scientific outputs, and a practical demonstration cell.

Awards

  • 2025: Faculty Research Award for PhD Students (UL-FRI)
  • 2024: Faculty Prešeren award from UNI-LJ for masters thesis
  • 2024: Faculty Research Award for PhD Students (UL-FRI)

Teaching

I am actively involved in teaching at the University of Ljubljana, Faculty of Computer and Information Science as a teaching assistant at:

  • Deep Learning (Globoko Učenje) – Ongoing

Service

Reviewer for CVPR, ECCV, ICCV, NeurIPS, ICLR, ICML, WACV and IJCV.


Publications

First author of papers published at CVPR, ECCV and ICCV. My full bibliography can be seen in my Google Scholar.

  •  
    AnomalyVFM - Transforming Vision Foundation Models into Zero-Shot Anomaly Detectors
    Matic Fučka, Vitjan Zavrtanik and Danijel Skočaj
    IEEE / CVF Computer Vision and Pattern Recognition Conference (CVPR), 2026
  •  
    ObjectCore - Efficient Few-shot Logical Anomaly Detection using Object Representations
    Matic Fučka, Vitjan Zavrtanik and Danijel Skočaj
    IEEE / CVF Winter Conference on Applications of Computer Vision (WACV), 2026
  •  
    PyramidCore -- Feature Pyramids for Few-Shot Logical Anomaly Detection
    Matic Fučka, Vitjan Zavrtanik and Danijel Skočaj
    2026 IEEE 23rd Mediterranean Electrotechnical Conference (MELECON), 2026
  •  
    Be the Change You Want to See: Revisiting Remote Sensing Change Detection Practices
    Blaž Rolih, Matic Fučka, Filip Wolf and Luka Čehovin Zajc
    IEEE Transactions on Geoscience and Remote Sensing, 2025
  •  
    Detekcija logičnih anomalij z uporabo velikih jezikovnih modelov
    Matic Fučka and Danijel Skočaj
    ERK 2025, 2025
  •  
    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
  •  
    SALAD -- Semantics-Aware Logical Anomaly Detection
    Matic Fučka, Vitjan Zavrtanik and Danijel Skočaj
    IEEE/CVF International Conference on Computer Vision (ICCV), 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
  •  
    TransFusion - A Transparency-Based Diffusion Model for Anomaly Detection
    Matic Fučka, Vitjan Zavrtanik and Danijel Skočaj
    European Conference on Computer Vision (ECCV), 2024
  •  
    3D-model-based Rendering of Synthetic Images For Training Segmentation Models in an Industrial Environment
    Matic Fučka, Marko Rus, Jakob Božič and Danijel Skočaj
    ROSUS 2023 - Računalniška obdelava slik in njena uporaba v Sloveniji 2023, 2023
Faculty of Computer and Information Science

Visual Cognitive Systems Laboratory

University of Ljubljana

Faculty of Computer and Information Science

Večna pot 113
SI-1000 Ljubljana
Slovenia
Tel.: +386 1 479 8245