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20172022
most citedFace Deidentification with Generative Deep Neural Networks

76 citations · 149 across the 9 of their papers we have counts for

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11 papers · 1 filter

cs.CV202262 cited

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…

cs.CV2022

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…

cs.CV20224 cited

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…

cs.CV2022

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…

cs.CV2022

Hierarchical Superquadric Decomposition with Implicit Space Separation

Jaka Šircelj, Peter Peer, Franc Solina +1

We introduce a new method to reconstruct 3D objects using a set of volumetric primitives, i.e., superquadrics. The method hierarchically decomposes a target 3D object into pairs of…

cs.CV20205 cited

Segmentation and Recovery of Superquadric Models using Convolutional Neural Networks

Jaka Šircelj, Tim Oblak, Klemen Grm +5

In this paper we address the problem of representing 3D visual data with parameterized volumetric shape primitives. Specifically, we present a (two-stage) approach built around con…