ProfessorsProfessors of Sveucilište u ZagrebuKristijan Bartol

Kristijan Bartol

Sveucilište u Zagrebu

H-index: 6

Europe-Croatia

About Kristijan Bartol

Kristijan Bartol, With an exceptional h-index of 6 and a recent h-index of 6 (since 2020), a distinguished researcher at Sveucilište u Zagrebu, specializes in the field of human mesh regression, deep learning, computer vision, 3D reconstruction.

His recent articles reflect a diverse array of research interests and contributions to the field:

Addressing the generalization of 3D registration methods with a featureless baseline and an unbiased benchmark

A Deep Learning Model for Estimation of Human Body Measurements from Images

Challenging the Universal Representation of Deep Models for 3D Point Cloud Registration

Generalizable Human Pose Triangulation

Linear regression vs. deep learning: A simple yet effective baseline for human body measurement

Can OpenPose Be Used as a 3D Registration Method for 3D Scans of Cultural Heritage Artifacts

Catadioptric Stereo on a Smartphone

A review of body measurement using 3D scanning

Kristijan Bartol Information

University	Sveucilište u Zagrebu
Position	Researcher Faculty of Electrical Engineering and Computing Department of
Citations(all)	138
Citations(since 2020)	138
Cited By	3
hIndex(all)	6
hIndex(since 2020)	6
i10Index(all)	4
i10Index(since 2020)	4
Email	Access Email
University Profile Page	Sveucilište u Zagrebu
Google Scholar	View Google Scholar Profile

Kristijan Bartol Skills & Research Interests

human mesh regression

deep learning

computer vision

3D reconstruction

Top articles of Kristijan Bartol

Title	Journal	Author(s)	Publication Date
Addressing the generalization of 3D registration methods with a featureless baseline and an unbiased benchmark	Machine vision and applications	David Bojanić Kristijan Bartol Josep Forest Tomislav Petković Tomislav Pribanić	2024/5
A Deep Learning Model for Estimation of Human Body Measurements from Images		Kristijan Bartol	2023/3/24
Challenging the Universal Representation of Deep Models for 3D Point Cloud Registration		David Bojanić Kristijan Bartol Josep Forest Stefan Gumhold Tomislav Petković ...	2022/11/29
Generalizable Human Pose Triangulation		Kristijan Bartol David Bojanić Tomislav Petković Tomislav Pribanić	2022
Linear regression vs. deep learning: A simple yet effective baseline for human body measurement	Sensors	Kristijan Bartol David Bojanić Tomislav Petković Stanislav Peharec Tomislav Pribanić	2022/2/28
Can OpenPose Be Used as a 3D Registration Method for 3D Scans of Cultural Heritage Artifacts		Tomislav Pribanić David Bojanić Kristijan Bartol Tomislav Petković	2021
Catadioptric Stereo on a Smartphone		Kristijan Bartol David Bojanić Tomislav Petković Tomislav Pribanić	2021/9/13
A review of body measurement using 3D scanning		Kristijan Bartol David Bojanić Tomislav Petković Tomislav Pribanić	2021/4/29
Towards keypoint guided self-supervised depth estimation	arXiv preprint arXiv:2011.03091	Kristijan Bartol David Bojanic Tomislav Petkovic Tomislav Pribanic Yago Diez Donoso	2020/11/5
A review of rigid 3D registration methods		David Bojanić Kristijan Bartol Tomislav Petković Tomislav Pribanić	2020
Evaluation of 3D Registration Deep Learning Methods Using Iterative Transformation Estimations		David Bojanić Kristijan Bartol Tomislav Petković Nicola D’Apuzzo Tomislav Pribanić	2020/11/15
Scene Adaptive Structured Light 3D Imaging.		Tomislav Pribanic Tomislav Petkovic David Bojanic Kristijan Bartol Mohit Gupta	2020
A Review Of 3D Human Pose Estimation From 2D Images		Kristijan Bartol David Bojanić Tomislav Petković Nicola D’Apuzzo Tomislav Pribanić	2020/11
Can Human Sex Be Learned Using Only 2D Body Keypoint Estimations?	arXiv preprint arXiv:2011.03104	Kristijan Bartol Tomislav Pribanic David Bojanic Tomislav Petkovic	2020/11/5
Smart Time-Multiplexing of Quads Solves the Multicamera Interference Problem		Tomislav Pribanic Tomislav Petkovic David Bojanic Kristijan Bartol	2020/11/5