By Associate Professor Piotr Koniusz

Preprints

Wang L; Liu J; Koniusz P, 2021, 3D Skeleton-based Few-shot Action Recognition with JEANIE is not so Naïve, https://arxiv.org/abs/2112.12668v1

Ni Y; Koniusz P; Hartley R; Nock R, 2021, Manifold Learning Benefits GANs, https://arxiv.org/abs/2112.12618v2

Lu C; Koniusz P, 2021, Few-shot Keypoint Detection with Uncertainty Learning for Unseen Species, https://arxiv.org/abs/2112.06183v3

Simon C; Koniusz P; Harandi M, 2021, Meta-Learning for Multi-Label Few-Shot Classification, https://arxiv.org/abs/2110.13494v1

Tas Y; Koniusz P, 2021, Simple Dialogue System with AUDITED, https://arxiv.org/abs/2110.11881v1

Simon C; Koniusz P; Petersson L; Han Y; Harandi M, 2021, Towards a Robust Differentiable Architecture Search under Label Noise, https://arxiv.org/abs/2110.12197v1

Wang L; Sun K; Koniusz P, 2021, High-order Tensor Pooling with Attention for Action Recognition, https://arxiv.org/abs/2110.05216v4

Zhu H; Koniusz P, 2021, REFINE: Random RangE FInder for Network Embedding, https://doi.org/10.1145/3459637.3482168

Zhu H; Koniusz P, 2021, Graph Convolutional Network with Generalized Factorized Bilinear Aggregation, https://arxiv.org/abs/2107.11666v1

Shao W; Prabowo A; Zhao S; Koniusz P; Salim FD, 2021, Predicting Flight Delay with Spatio-Temporal Trajectory Convolutional Network and Airport Situational Awareness Map, http://dx.doi.org/10.48550/arxiv.2105.08969

Koniusz P; Wang L; Cherian A, 2020, Tensor Representations for Action Recognition, https://doi.org/10.1109/TPAMI.2021.3107160

Koniusz P; Zhang H, 2020, Power Normalizations in Fine-grained Image, Few-shot Image and Graph Classification, https://doi.org/10.1109/TPAMI.2021.3107164

Hou W; Suominen H; Koniusz P; Caldwell S; Gedeon T, 2020, A Token-wise CNN-based Method for Sentence Compression, http://dx.doi.org/10.48550/arxiv.2009.11260

Wang X; Salim FD; Ren Y; Koniusz P, 2020, Relation Embedding for Personalised POI Recommendation, http://dx.doi.org/10.48550/arxiv.2002.03461

Yu X; Zhuang Z; Koniusz P; Li H, 2020, 6DoF Object Pose Estimation via Differentiable Proxy Voting Loss, https://arxiv.org/abs/2002.03923v2

Wang L; Koniusz P, 2020, Self-supervising Action Recognition by Statistical Moment and Subspace Descriptors, https://doi.org/10.1145/3474085.3475572

Zhang H; Zhang L; Qi X; Li H; Torr PHS; Koniusz P, 2020, Few-shot Action Recognition with Permutation-invariant Attention, https://arxiv.org/abs/2001.03905v3

Zhang H; Koniusz P; Jian S; Li H; Torr PHS, 2020, Rethinking Class Relations: Absolute-relative Supervised and Unsupervised Few-shot Learning, https://arxiv.org/abs/2001.03919v4

Zhang H; Torr PHS; Koniusz P, 2020, Improving Few-shot Learning by Spatially-aware Matching and CrossTransformer, https://arxiv.org/abs/2001.01600v2

Prabowo A; Koniusz P; Shao W; Salim FD, 2019, COLTRANE: ConvolutiOnaL TRAjectory NEtwork for Deep Map Inference, http://dx.doi.org/10.48550/arxiv.1909.11048

Wang L; Huynh DQ; Koniusz P, 2019, A Comparative Review of Recent Kinect-based Action Recognition Algorithms, https://doi.org/10.1109/TIP.2019.2925285

Wang L; Koniusz P; Huynh DQ, 2019, Hallucinating IDT Descriptors and I3D Optical Flow Features for Action Recognition with CNNs, https://arxiv.org/abs/1906.05910v2

Koniusz P; Zhang H; Porikli F, 2018, A Deeper Look at Power Normalizations, https://arxiv.org/abs/1806.09183v1

Zhang R; Tas Y; Koniusz P, 2018, Artwork Identification from Wearable Camera Images for Enhancing Experience of Museum Audiences, https://arxiv.org/abs/1806.09084v1

Tas Y; Koniusz P, 2018, CNN-based Action Recognition and Supervised Domain Adaptation on 3D Body Skeletons via Kernel Feature Maps, https://arxiv.org/abs/1806.09078v1

Shiri F; Yu X; Porikli F; Koniusz P, 2018, Face Destylization, https://arxiv.org/abs/1802.01237v1

Zhang H; Koniusz P, 2018, Zero-Shot Kernel Learning, https://arxiv.org/abs/1802.01279v2

Koniusz P; Tas Y; Zhang H; Harandi M; Porikli F; Zhang R, 2018, Museum Exhibit Identification Challenge for Domain Adaptation and Beyond, https://arxiv.org/abs/1802.01093v1

Shiri F; Yu X; Porikli F; Hartley R; Koniusz P, 2018, Identity-preserving Face Recovery from Portraits, https://arxiv.org/abs/1801.02279v2

Cherian A; Koniusz P; Gould S, 2017, Higher-order Pooling of CNN Features via Kernel Linearization for Action Recognition, https://arxiv.org/abs/1701.05432v1

Koniusz P; Tas Y; Porikli F, 2016, Domain Adaptation by Mixture of Alignments of Second- or Higher-Order Scatter Tensors, https://arxiv.org/abs/1611.08195v2

Koniusz P; Cherian A; Porikli F, 2016, Tensor Representations via Kernel Linearization for Action Recognition from 3D Skeletons (Extended Version), https://arxiv.org/abs/1604.00239v2

Koniusz P; Cherian A, 2015, Dictionary Learning and Sparse Coding for Third-order Super-symmetric Tensors, https://arxiv.org/abs/1509.02970v1

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