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20172022
most citedFace Deidentification with Generative Deep Neural Networks

76 citations · 83 across the 6 of their papers we have counts for

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9 papers · 1 filter

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.CV2022

Assessing Bias in Face Image Quality Assessment

Žiga Babnik, Vitomir Štruc

Face image quality assessment (FIQA) attempts to improve face recognition (FR) performance by providing additional information about sample quality. Because FIQA methods attempt to…

cs.CV2022

A Survey on Computer Vision based Human Analysis in the COVID-19 Era

Fevziye Irem Eyiokur, Alperen Kantarcı, Mustafa Ekrem Erakın +8

The emergence of COVID-19 has had a global and profound impact, not only on society as a whole, but also on the lives of individuals. Various prevention measures were introduced ar…

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…

cs.CV2019

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…

cs.CV20192 cited

The Unconstrained Ear Recognition Challenge 2019 - ArXiv Version With Appendix

Žiga Emeršič, Aruna Kumar S. V., B. S. Harish +28

This paper presents a summary of the 2019 Unconstrained Ear Recognition Challenge (UERC), the second in a series of group benchmarking efforts centered around the problem of person…