activity
20172026
most citedStrengths and Weaknesses of Deep Learning Models for Face Recognition Against Image Degradations

217 citations · 235 across the 7 of their papers we have counts for

collaborators

10 papers

cs.CV2026

SCOUT: Semantic Concept Discovery for Open-Vocabulary Editing of face Recognition Templates

Leon Todorov, Peter Rot, Peter Peer +2

Face recognition templates are compact identity representations, yet they also encode rich semantic information about facial appearance. Prior work has shown that templates can be…

cs.CV2023

EFaR 2023: Efficient Face Recognition Competition

Jan Niklas Kolf, Fadi Boutros, Jurek Elliesen +24

This paper presents the summary of the Efficient Face Recognition Competition (EFaR) held at the 2023 International Joint Conference on Biometrics (IJCB 2023). The competition rece…

cs.CV2022

Meet-in-the-middle: Multi-scale upsampling and matching for cross-resolution face recognition

Klemen Grm, Berk Kemal Özata, Vitomir Štruc +1

In this paper, we aim to address the large domain gap between high-resolution face images, e.g., from professional portrait photography, and low-quality surveillance images, e.g.,…

cs.CV2021

MFR 2021: Masked Face Recognition Competition

Fadi Boutros, Naser Damer, Jan Niklas Kolf +32

This paper presents a summary of the Masked Face Recognition Competitions (MFR) held within the 2021 International Joint Conference on Biometrics (IJCB 2021). The competition attra…

cs.CV2020★ 5 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…

cs.CV2019★ 1 cited

Recovery of Superquadrics from Range Images using Deep Learning: A Preliminary Study

Tim Oblak, Klemen Grm, Aleš Jaklič +3

It has been a longstanding goal in computer vision to describe the 3D physical space in terms of parameterized volumetric models that would allow autonomous machines to understand…