activity
20242026
most citedBe the Change You Want to See: Revisiting Remote Sensing Change Detection Practices

14 citations · 23 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2026

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…

cs.CV2026

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…

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★ 14 cited

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.…