14 citations · 25 across the 8 of their papers we have counts for
8 papers
ChangeFlow -- Latent Rectified Flow for Change Detection in Remote Sensing
Blaž Rolih, Matic Fučka, Filip Wolf +1
Remote sensing change detection (RSCD) localises changes between two images of the same geographic region. Most state-of-the-art methods are trained with a per-pixel discriminative…
Make Some Noise: Unsupervised Remote Sensing Change Detection Using Latent Space Perturbations
Blaž Rolih, Matic Fučka, Filip Wolf +1
Unsupervised remote sensing change detection (UCD) aims to localise changes between two images of the same region without relying on labelled training data. Most recent approaches…
AnomalyVFM -- Transforming Vision Foundation Models into Zero-Shot Anomaly Detectors
Matic Fučka, Vitjan Zavrtanik, Danijel Skočaj
Zero-shot anomaly detection aims to detect and localise abnormal regions in the image without access to any in-domain training images. While recent approaches leverage vision-langu…
SALAD -- Semantics-Aware Logical Anomaly Detection
Matic Fučka, Vitjan Zavrtanik, Danijel Skočaj
Recent surface anomaly detection methods excel at identifying structural anomalies, such as dents and scratches, but struggle with logical anomalies, such as irregular or missing o…
No Label Left Behind: A Unified Surface Defect Detection Model for all Supervision Regimes
Blaž Rolih, Matic Fučka, Danijel Skočaj
Surface defect detection is a critical task across numerous industries, aimed at efficiently identifying and localising imperfections or irregularities on manufactured components.…
Be the Change You Want to See: Revisiting Remote Sensing Change Detection Practices
Blaž Rolih, Matic Fučka, Filip Wolf +1
Remote sensing change detection aims to localize semantic changes between images of the same location captured at different times. In the past few years, newer methods have attribu…
SuperSimpleNet: Unifying Unsupervised and Supervised Learning for Fast and Reliable Surface Defect Detection
Blaž Rolih, Matic Fučka, Danijel Skočaj
The aim of surface defect detection is to identify and localise abnormal regions on the surfaces of captured objects, a task that's increasingly demanded across various industries.…
TransFusion -- A Transparency-Based Diffusion Model for Anomaly Detection
Matic Fučka, Vitjan Zavrtanik, Danijel Skočaj
Surface anomaly detection is a vital component in manufacturing inspection. Current discriminative methods follow a two-stage architecture composed of a reconstructive network foll…