13 citations · 33 across the 5 of their papers we have counts for
5 papers
Dense Center-Direction Regression for Object Counting and Localization with Point Supervision
Domen Tabernik, Jon Muhovič, Danijel Skočaj
Object counting and localization problems are commonly addressed with point supervised learning, which allows the use of less labor-intensive point annotations. However, learning b…
Center Direction Network for Grasping Point Localization on Cloths
Domen Tabernik, Jon Muhovič, Matej Urbas +1
Object grasping is a fundamental challenge in robotics and computer vision, critical for advancing robotic manipulation capabilities. Deformable objects, like fabrics and cloths, p…
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.…
Cheating Depth: Enhancing 3D Surface Anomaly Detection via Depth Simulation
Vitjan Zavrtanik, Matej Kristan, Danijel Skočaj
RGB-based surface anomaly detection methods have advanced significantly. However, certain surface anomalies remain practically invisible in RGB alone, necessitating the incorporati…
DSR -- A dual subspace re-projection network for surface anomaly detection
Vitjan Zavrtanik, Matej Kristan, Danijel Skočaj
The state-of-the-art in discriminative unsupervised surface anomaly detection relies on external datasets for synthesizing anomaly-augmented training images. Such approaches are pr…