217 citations · 467 across the 20 of their papers we have counts for
6 papers · 1 filter
Training Convolutional Neural Networks with Limited Training Data for Ear Recognition in the Wild
Žiga Emeršič, Dejan Štepec, Vitomir Štruc +1
Identity recognition from ear images is an active field of research within the biometric community. The ability to capture ear images from a distance and in a covert manner makes e…
Strengths and Weaknesses of Deep Learning Models for Face Recognition Against Image Degradations
Klemen Grm, Vitomir Štruc, Anais Artiges +2
Deep convolutional neural networks (CNNs) based approaches are the state-of-the-art in various computer vision tasks, including face recognition. Considerable research effort is cu…
UG^2: a Video Benchmark for Assessing the Impact of Image Restoration and Enhancement on Automatic Visual Recognition
Rosaura G. Vidal, Sreya Banerjee, Klemen Grm +2
Advances in image restoration and enhancement techniques have led to discussion about how such algorithmscan be applied as a pre-processing step to improve automatic visual recogni…
The Unconstrained Ear Recognition Challenge
Žiga Emeršič, Dejan Štepec, Vitomir Štruc +11
In this paper we present the results of the Unconstrained Ear Recognition Challenge (UERC), a group benchmarking effort centered around the problem of person recognition from ear i…
Face Deidentification with Generative Deep Neural Networks
Blaž Meden, Refik Can Mallı, Sebastjan Fabijan +3
Face deidentification is an active topic amongst privacy and security researchers. Early deidentification methods relying on image blurring or pixelization were replaced in recent…
Pixel-wise Ear Detection with Convolutional Encoder-Decoder Networks
Žiga Emeršič, Luka Lan Gabriel, Vitomir Štruc +1
Object detection and segmentation represents the basis for many tasks in computer and machine vision. In biometric recognition systems the detection of the region-of-interest (ROI)…