Piotr Koniusz

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Citations	5591	4984
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Hongguang ZhangAustralian National University, Data61/CSIROVerified email at alumni.anu.edu.au
Hao ZhuData61@CSIROVerified email at data61.csiro.au
Lei WangAustralian National University, Data61/CSIROVerified email at anu.edu.au
Hongdong LiProfessor of Computer Vision and Learning, Australian National UniversityVerified email at anu.edu.au
Mehrtash HarandiDepartment of Electrical and Computer Systems Engineering, Monash UniversityVerified email at monash.edu
Fatih PorikliQualcomm, Australian National UniversityVerified email at anu.edu.au
Christian SimonSonyVerified email at sony.com
Krystian MikolajczykProfessor, Imperial College LondonVerified email at imperial.ac.uk
Richard NockGoogle ResearchVerified email at uniagro.fr
Philip TorrProfessor, University of OxfordVerified email at eng.ox.ac.uk
Yusuf TasResearch Student, Australia National UniversityVerified email at anu.edu.au
Lei WangSchool of Computing and Information Technology, University of WollongongVerified email at uow.edu.au
Yifei ZHANG (张逸飞)Research Scientist, Nanyang Technological UniversityVerified email at cse.cuhk.edu.hk
Irwin KingThe Chinese University of Hong KongVerified email at cse.cuhk.edu.hk
Anoop CherianMitsubishi Electric Research Labs (MERL), Australian National UniversityVerified email at merl.com
Flora SalimProfessor, Cisco Chair of AI & Digital Transport, Computer Science and Engineering, UNSWVerified email at unsw.edu.au
Yuchao Dai (戴玉超)Northwestern Polytechnical UniversityVerified email at nwpu.edu.cn
Xin YuThe University of QueenslandVerified email at uq.edu.au
Arian PrabowoUniversity of New South WalesVerified email at unsw.edu.au
Du HuynhThe University of Western AustraliaVerified email at uwa.edu.au

Piotr Koniusz

Other namesPeter Koniusz

Principal Res. Scientist (Data61❤CSIRO). Hon. Associate Professor (level D) (ANU).

Verified email at anu.edu.au - Homepage

Computer Vision Machine Learning Recognition Tensor and Kernel Methods Neural Networks


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Deep stacked hierarchical multi-patch network for image deblurring H Zhang, Y Dai, H Li, P Koniusz Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019	615	2019
Convolutional Kernel Networks J Mairal, P Koniusz, Z Harchaoui, C Schmid Advances Neural Information Processing Systems (NIPS), 2014	475	2014
Adaptive Subspaces for Few-Shot Learning C Simon, P Koniusz, R Nock, M Harandi Computer Vision and Pattern Recognition (CVPR), 2020	469	2020
Simple Spectral Graph Convolution H Zhu, P Koniusz International Conference on Learning Representations (ICLR), 2021	312	2021
Few-Shot Learning via Saliency-guided Hallucination of Samples H Zhang, J Zhang, P Koniusz IEEE Computer Vision and Pattern Recognition (CVPR), 2019	261	2019
A Comparative Review of Recent Kinect-basedAction Recognition Algorithms L Wang, DQ Huynh, P Koniusz IEEE Transactions on Image Processing (TIP), 2019	252	2019
Few-shot Action Recognition with Permutation-invariant Attention H Zhang, L Zhang, X Qi, H Li, PHS Torr, P Koniusz European Conference on Computer Vision (ECCV), 2020	185	2020
Domain Adaptation by Mixture of Alignments of Second- or Higher-Order Scatter Tensors P Koniusz, Y Tas, F Porikli Computer Vision and Pattern Recognition, 2017	152	2017
Tensor Representations via Kernel Linearization for Action Recognition from 3D Skeletons P Koniusz, A Cherian, F Porikli European Conference on Computer Vision, 2016	151	2016
Higher-order occurrence pooling for bags-of-words: Visual concept detection P Koniusz, F Yan, PH Gosselin, K Mikolajczyk IEEE transactions on pattern analysis and machine intelligence 39 (2), 313-326, 2017	131	2017
Zero-Shot Kernel Learning H Zhang, P Koniusz The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 7670-7679, 2018	123	2018
On Learning the Geodesic Path for Incremental Learning C Simon, P Koniusz, M Harandi Computer Vision and Pattern Recognition (CVPR), 2021	120	2021
Hallucinating IDT Descriptors and I3D Optical Flow Features for Action Recognition with CNNs L Wang, P Koniusz, DQ Huynh International Conference on Computer Vision (ICCV), 2019	116	2019
COSTA: Covariance-Preserving Feature Augmentation for Graph Contrastive Learning Y Zhang, H Zhu, Z Song, P Koniusz, I King International Conference on Knowledge Discovery and Data Mining (KDD 2022), 2022	104	2022
Comparison of mid-level feature coding approaches and pooling strategies in visual concept detection P Koniusz, F Yan, K Mikolajczyk Computer vision and image understanding 117 (5), 479-492, 2013	103	2013
Rethinking Class Relations: Absolute-relative Supervised and Unsupervised Few-shot Learning H Zhang, P Koniusz, S Jian, H Li, PHS Torr Computer Vision and Pattern Recognition (CVPR), 2021	70	2021
Spectral Feature Augmentation for Graph Contrastive Learning and Beyond Y Zhang, H Zhu, Z Song, P Koniusz, I King International Conference on Artificial Intelligence (AAAI), 2023, arXiv …, 2022	69	2022
Power Normalizing Second-order Similarity Network for Few-shot Learning H Zhang, P Koniusz IEEE Winter Conference on Applications of Computer Vision (WACV), 2019	67	2019
6DoF Object Pose Estimation via Differentiable Proxy Voting Regularizer. X Yu, Z Zhuang, P Koniusz, H Li The British Machine Vision Conference (BMVC), 1-13, 2020	63*	2020
On modulating the gradient for meta-learning C Simon, P Koniusz, R Nock, M Harandi Proceedings of the European Conference on Computer Vision (ECCV), 2020	63	2020

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