Cedric Scheerlinck - Google Scholar

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	All	Since 2015
Citations	80	80
h-index	5	5
i10-index	4	4

2018201920202 30 48

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Nick BarnesAssociate Professor, Australian National UniversityVerified email at anu.edu.au
Robert MahonyAustralian National UniversityVerified email at anu.edu.au
Davide ScaramuzzaProfessor of Robotics and Perception, University of ZurichVerified email at ifi.uzh.ch
Xin YuPhD, The University of Technology Sydney (UTS)Verified email at uts.edu.au
Richard HartleyAustralian National University, National ICT Australia (NICTA)Verified email at anu.edu.au
Yuchao Dai (戴玉超)Northwestern Polytechnical UniversityVerified email at nwpu.edu.cn
Miaomiao LiuAustralian National UniversityVerified email at anu.edu.au
Liyuan PanAustralian National UniversityVerified email at anu.edu.au
Henri RebecqResearch Scientist, GoogleVerified email at google.com
Timo StoffregenPhD Student, Monash UniversityVerified email at monash.edu
Daniel GehrigPh.D. candidate, University of ZurichVerified email at ifi.uzh.ch
Andrew OoiThe University of MelbourneVerified email at unimelb.edu.au
Eric K. W. PoonThe University of MelbourneVerified email at unimelb.edu.au
Cheng (Rey) ChinThe University of AdelaideVerified email at adelaide.edu.au
Vikas ThondapuResearch Fellow, Massachusetts General Hospital, Harvard Medical SchoolVerified email at mgh.harvard.edu

Cedric Scheerlinck

PhD Candidate, Australian National University

Verified email at anu.edu.au - Homepage

Computer Vision Event-based Vision Robotics Computational Fluid Dynamics


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Continuous-time intensity estimation using event cameras C Scheerlinck, N Barnes, R Mahony Asian Conference on Computer Vision, 308-324, 2018	35	2018
High Frame Rate Video Reconstruction based on an Event Camera L Pan, R Hartley, C Scheerlinck, M Liu, X Yu, Y Dai arXiv preprint arXiv:1903.06531, 2019	16*	2019
Bringing a blurry frame alive at high frame-rate with an event camera L Pan, C Scheerlinck, X Yu, R Hartley, M Liu, Y Dai Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2019	16	2019
Asynchronous spatial image convolutions for event cameras C Scheerlinck, N Barnes, R Mahony IEEE Robotics and Automation Letters 4 (2), 816-822, 2019	10	2019
CED: color event camera dataset C Scheerlinck, H Rebecq, T Stoffregen, N Barnes, R Mahony, ... Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2019	10	2019
Fast image reconstruction with an event camera C Scheerlinck, H Rebecq, D Gehrig, N Barnes, R Mahony, D Scaramuzza The IEEE Winter Conference on Applications of Computer Vision, 156-163, 2020	7	2020
How to Train Your Event Camera Neural Network T Stoffregen, C Scheerlinck, D Scaramuzza, T Drummond, N Barnes, ... arXiv preprint arXiv:2003.09078, 2020	2	2020
Effect of Medical Imaging Modalities on the simulated blood flow through a 3D reconstructed stented coronary artery segment C Scheerlinck, C Mamon, T Zahtila, W Nguyen, E Poon, V Thondapu, ... Australasian Fluid Mechanics Conference, 2016		2016
Computational fluid dynamics comparisons of wall shear stress in patient-specific coronary artery bifurcation using coronary angiography and optical coherence tomography E Poon, V Thondapu, C Chin, C Scheerlinck, T Zahtila, C Mamon, ... APS, H15. 008, 2016		2016

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