8 citations · 9 across the 2 of their papers we have counts for
3 papers
cs.CV2025★ 8 cited
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.…
cs.CV2025
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…
cs.CV2024★ 1 cited
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.…