106 citations · 311 across the 22 of their papers we have counts for
10 papers · 1 filter
Body Segmentation Using Multi-task Learning
Julijan Jug, Ajda Lampe, Vitomir Štruc +1
Body segmentation is an important step in many computer vision problems involving human images and one of the key components that affects the performance of all downstream tasks. S…
C-VTON: Context-Driven Image-Based Virtual Try-On Network
Benjamin Fele, Ajda Lampe, Peter Peer +1
Image-based virtual try-on techniques have shown great promise for enhancing the user-experience and improving customer satisfaction on fashion-oriented e-commerce platforms. Howev…
FaceQAN: Face Image Quality Assessment Through Adversarial Noise Exploration
Žiga Babnik, Peter Peer, Vitomir Štruc
Recent state-of-the-art face recognition (FR) approaches have achieved impressive performance, yet unconstrained face recognition still represents an open problem. Face image quali…
PrivacyProber: Assessment and Detection of Soft-Biometric Privacy-Enhancing Techniques
Peter Rot, Peter Peer, Vitomir Štruc
Soft-biometric privacy-enhancing techniques represent machine learning methods that aim to: (i) mitigate privacy concerns associated with face recognition technology by suppressing…
GlassesGAN: Eyewear Personalization using Synthetic Appearance Discovery and Targeted Subspace Modeling
Richard Plesh, Peter Peer, Vitomir Štruc
We present GlassesGAN, a novel image editing framework for custom design of glasses, that sets a new standard in terms of image quality, edit realism, and continuous multi-style ed…
SeeABLE: Soft Discrepancies and Bounded Contrastive Learning for Exposing Deepfakes
Nicolas Larue, Ngoc-Son Vu, Vitomir Struc +2
Modern deepfake detectors have achieved encouraging results, when training and test images are drawn from the same data collection. However, when these detectors are applied to ima…