Vitomir Štruc

Vitomir Štruc
University of Ljubljana · Faculty of Electrical Engineering

PhD

About

181
Publications
79,215
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2,946
Citations
Additional affiliations
July 2011 - June 2020
University of Ljubljana
Position
  • Professor (Associate)

Publications

Publications (181)
Article
Full-text available
In this paper we address the problem of hallucinating high-resolution facial images from low-resolution inputs at high magnification factors. We approach this task with convolutional neural networks (CNNs) and propose a novel (deep) face hallucination model that incorporates identity priors into the learning procedure. The model consists of two mai...
Article
Full-text available
The area of ocular biometrics is among the most popular branches of biometric recognition technology. This area has long been dominated by iris recognition research, while other ocular modalities such as the periocular region or the vasculature of the sclera have received significantly less attention in the literature. Consequently, ocular modaliti...
Article
Full-text available
The new Coronavirus disease (COVID-19) has seriously affected the world. By the end of November 2020, the global number of new coronavirus cases had already exceeded 60 million and the number of deaths 1,410,378 according to information from the World Health Organization (WHO). To limit the spread of the disease, mandatory face-mask rules are now b...
Article
Full-text available
Biometric recognition technology has made significant advances over the last decade and is now used across a number of services and applications. However, this widespread deployment has also resulted in privacy concerns and evolving societal expectations about the appropriate use of the technology. For example, the ability to automatically extract...
Article
Full-text available
The task of reconstructing 3D scenes based on visual data represents a longstanding problem in computer vision. Common reconstruction approaches rely on the use of multiple volumetric primitives to describe complex objects. Superquadrics (a class of volumetric primitives) have shown great promise due to their ability to describe various shapes with...
Preprint
Images of morphed faces pose a serious threat to face recognition--based security systems, as they can be used to illegally verify the identity of multiple people with a single morphed image. Modern detection algorithms learn to identify such morphing attacks using authentic images of real individuals. This approach raises various privacy concerns...
Preprint
Current state-of-the-art segmentation techniques for ocular images are critically dependent on large-scale annotated datasets, which are labor-intensive to gather and often raise privacy concerns. In this paper, we present a novel framework, called BiOcularGAN, capable of generating synthetic large-scale datasets of photorealistic (visible light an...
Preprint
Full-text available
Efficient load forecasting is needed to ensure better observability in the distribution networks, whereas such forecasting is made possible by an increasing number of smart meter installations. Because distribution networks include a large amount of different loads at various aggregation levels, such as individual consumers, transformer stations an...
Article
Full-text available
Most commercially successful face recognition systems combine information from multiple sensors (2D and 3D, visible light and infrared, etc.) to achieve reliable recognition in various environments. When only a single sensor is available, the robustness as well as efficacy of the recognition process suffer. In this paper, we focus on face recogniti...
Conference Paper
Segmentacija je pomemben del številnih problemov računalniškega vida, ki vključujejo človeške podobe, in je ena ključnih komponent, ki vpliva na uspešnost vseh nadaljnjih nalog. Več predhodnih del je ta problem obravnavalo z uporabo večciljnega modela, ki izkorišča korelacije med različnimi nalogami za izboljšanje uspešnosti segmentacije. Na podlag...
Chapter
Full-text available
Recently, digital face manipulation and its detection have sparked large interest in industry and academia around the world. Numerous approaches have been proposed in the literature to create realistic face manipulations, such as DeepFakes and face morphs. To the human eye manipulated images and videos can be almost indistinguishable from real cont...
Article
Full-text available
In the recent past, different researchers have proposed privacy-enhancing face recognition systems designed to conceal soft-biometric attributes at feature level. These works have reported impressive results, but generally did not consider specific attacks in their analysis of privacy protection. We introduce an attack on said schemes based on two...
Article
Full-text available
In the past few years, there has been a leap from traditional palmprint recognition methodologies, which use handcrafted features, to deep-learning approaches that are able to automatically learn feature representations from the input data. However, the information that is extracted from such deep-learning models typically corresponds to the global...
Article
V strokovni literaturi se vse pogosteje pojavljajo potrebe po metodah za zagotavljanje zasebnosti v slikovnih podatkih. Na področju analize obrazov so raziskovalci predlagali metode, ki preslikajo sliko obraza tako, da je samodejno luščenje mehkih biometričnih lastnosti oteženo, obenem pa je vizualni videz slike podoben izvirni sliki. V tem članku...
Article
V strokovni literaturi se vse pogosteje pojavljajo potrebe po metodah za zagotavljanje zasebnosti v slikovnih podatkih. Na področju analize obrazov so raziskovalci predlagali metode, ki preslikajo sliko obraza tako, da je samodejno luščenje mehkih biometričnih lastnosti oteženo, obenem pa je vizualni videz slike podoben izvirni sliki. V tem članku...
Preprint
Full-text available
In the recent past, different researchers have proposed novel privacy-enhancing face recognition systems designed to conceal soft-biometric information at feature level. These works have reported impressive results, but usually do not consider specific attacks in their analysis of privacy protection. In most cases, the privacy protection capabiliti...
Article
Recent years have seen considerable advances in biometric recognition techniques leading to a wide-spread deployment of biometric technology across a number of application domains, ranging from security, border control, and criminal investigations to entertainment, social media, autonomous driving and even health services. To highlight some of thes...
Preprint
Full-text available
We propose a novel reconstruction-based model for anomaly detection, called Y-GAN. The model consists of a Y-shaped auto-encoder and represents images in two separate latent spaces. The first captures meaningful image semantics, key for representing (normal) training data, whereas the second encodes low-level residual image characteristics. To ensu...
Chapter
Finite-state transducers are suitable for compact representation of pronunciation dictionaries, which are an important component of speech synthesis systems. In this paper, we first revise and analyse several properties of finite state transducers regarding their size minimization, which can be achieved by their determinization and minimisation. In...
Conference Paper
Full-text available
For iris recognition in non-cooperative environments, iris segmentation has been regarded as the first most important challenge still open to the biometric community, affecting all downstream tasks from normalization to recognition. In recent years, deep learning technologies have gained significant popularity among various computer vision tasks an...
Preprint
Full-text available
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 attracted a total of 10 participating teams with valid submissions. The affiliations of these teams are diverse and associated with academia and industry in nine different cou...
Preprint
Full-text available
Face editing is a popular research topic in the computer vision community that aims to edit a specific characteristic of a face image. Recent proposed methods are based on either training a conditional encoder-decoder Generative Adversarial Network (GAN) in an end-to-end fashion or on defining an operation in the latent space of a pre-trained vanil...
Article
Full-text available
Ear detection represents one of the key components of contemporary ear recognition systems. While significant progress has been made in the area of ear detection over recent years, most of the improvements are direct results of advances in the field of visual object detection. Only a limited number of techniques presented in the literature are doma...
Article
Prepoznava ljudi je temeljni problem, s katerim se ukvarja področje biometrije. V našem delu se ukvarjamo s prepoznavo beločničnih žilnih struktur, ki imajo številne prednosti pred ostalimi značilkami: beločnične žile so edinstvene, tudi med identičnimi dvojčki – celo bolj kot prstni odtisi; za zajem ne potrebujemo posebnih naprav, le običajen foto...
Article
Prepoznava ljudi je temeljni problem, s katerim se ukvarja področje biometrije. V našem delu se ukvarjamo s prepoznavo beločničnih žilnih struktur, ki imajo številne prednosti pred ostalimi značilkami: beločnične žile so edinstvene, tudi med identičnimi dvojčki – celo bolj kot prstni odtisi; za zajem ne potrebujemo posebnih naprav, le običajen foto...
Article
Full-text available
Face alignment (or facial landmarking) is an important task in many face-related applications, ranging from registration, tracking, and animation to higher-level classification problems such as face, expression, or attribute recognition. While several solutions have been presented in the literature for this task so far, reliably locating salient fa...
Article
Full-text available
Reconstruction of 3D space from visual data has always been a significant challenge in the field of computer vision. A popular approach to address this problem can be found in the form of bottom-up reconstruction techniques which try to model complex 3D scenes through a constellation of volumetric primitives. Such techniques are inspired by the cur...
Article
Full-text available
>>> Springer Nature SharedIt initiative publicly shares a full-text view-only version of the paper by using the link https://rdcu.be/Os7a! >>> Ear recognition technology has long been dominated by (local) descriptor-based techniques due to their formidable recognition performance and robustness to various sources of image variability. While deep-le...
Article
Full-text available
Research on soft-biometrics showed that privacy-sensitive information can be deduced from biometric data. Utilizing biometric templates only, information about a persons gender, age, ethnicity, sexual orientation, and health state can be deduced. For many applications, these templates are expected to be used for recognition purposes only. Thus, ext...
Chapter
In this chapter we address the problem of biometric identity recognition from the vasculature of the human sclera. Specifically, we focus on the challenging task of multi-view sclera recognition, where the visible part of the sclera vasculature changes from image to image due to varying gaze (or view) directions. We propose a complete solution for...
Chapter
This chapter introduces COM-Ear, a deep constellation model for ear recognition. Different from competing solutions, COM-Ear encodes global as well as local characteristics of ear images and generates descriptive ear representations that ensure competitive recognition performance. The model is designed as dual-path convolutional neural network (CNN...
Preprint
Full-text available
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 convolutional neural networks (CNNs) capable of segmenting complex depth scenes into the simpler geometric structures that can be represented with superquadric models. In th...
Conference Paper
Full-text available
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 recognition from ear images captured in uncontrolled settings. The goal of the challenge is to assess the performance of existing ear recognition techniques on a challen...
Conference Paper
See https://www.researchgate.net/publication/330726463_Influence_of_segmentation_on_deep_iris_recognition_performance
Preprint
Full-text available
Face alignment (or facial landmarking) is an important task in many face-related applications, ranging from registration, tracking and animation to higher-level classification problems such as face, expression or attribute recognition. While several solutions have been presented in the literature for this task so far, reliably locating salient faci...
Preprint
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 and interact with their surroundings. Such models are typically motivated by human visual perception and aim to represents all elements of the physical word ranging from...
Preprint
Full-text available
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 recognition from ear images captured in uncontrolled settings. The goal of the challenge is to assess the performance of existing ear recognition techniques on a challen...
Article
Full-text available
>>> Springer Nature SharedIt initiative publicly shares a full-text view-only version of the paper by using the link http://rdcu.be/BfJP! >>> The use of human gait as the means of biometric identification has gained a lot of attention in the past few years, mostly due to its enormous potential. Such biometrics can be captured at public places from...
Preprint
Full-text available
Despite the rise of deep learning in numerous areas of computer vision and image processing, iris recognition has not benefited considerably from these trends so far. Most of the existing research on deep iris recognition is focused on new models for generating discriminative and robust iris representations and relies on methodologies akin to tradi...
Chapter
Ear recognition has seen multiple improvements in recent years and still remains very active today. However, it has been approached from recognition and detection perspective separately. Furthermore, deep-learning-based approaches that are popular in other domains have seen limited use in ear recognition and even more so in ear detection. Moreover,...
Chapter
Full-text available
The Visual Object Tracking challenge VOT2018 is the sixth annual tracker benchmarking activity organized by the VOT initiative. Results of over eighty trackers are presented; many are state-of-the-art trackers published at major computer vision conferences or in journals in the recent years. The evaluation included the standard VOT and other popula...
Article
The paper proposes an augmented reality system for visual object verification that helps warehouse workers perform their work. The system sequentially captures images of objects that the warehouse workers encounter during their work and verifies whether the objects are the ones that the workers are supposed to fetch from storage. The system uses An...
Preprint
Full-text available
Contemporary face hallucination (FH) models exhibit considerable ability to reconstruct high-resolution (HR) details from low-resolution (LR) face images. This ability is commonly learned from examples of corresponding HR-LR image pairs, created by artificially down-sampling the HR ground truth data. This down-sampling (or degradation) procedure no...
Preprint
Full-text available
In this paper we address the problem of hallucinating high-resolution facial images from unaligned low-resolution inputs at high magnification factors. We approach the problem with convolutional neural networks (CNNs) and propose a novel (deep) face hallucination model that incorporates identity priors into the learning procedure. The model consist...
Article
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) is one of the most crucial steps in the processing pipeline, significantly impacting the performance of the entire recognition system. Existing approaches to ear detecti...
Article
Full-text available
Biometric technology has seen steady growth in deployment over the last decades. This growth is spurred by the increasing need for secure and convenient authentication schemes, surveillance applications and forensics among others. Recognition technology based on established biometric modalities, such as faces or fingerprints, is well studied and it...
Article
Performing covert biometric recognition in surveillance environments has been regarded as a grand challenge, considering the adversity of the conditions where recognition should be carried out (e.g., poor resolution, bad lighting, off-pose and partially occluded data). This special issue compiles a group of approaches to this problem.
Conference Paper
Full-text available
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 recognition. In principle, techniques like deblurring and super-resolution should yield improvements by de-emphasizing noise and increasing signal in an input image. But the his...