By Associate Professor Piotr Koniusz

Conference Papers

Zhang Y; Zhu H; Song Z; Chen Y; Fu X; Meng Z; Koniusz P; King I, 2024, 'Geometric View of Soft Decorrelation in Self-Supervised Learning', in Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 4338 - 4349, http://dx.doi.org/10.1145/3637528.3671914

Lu C; Koniusz P, 2024, 'Detect Any Keypoints: An Efficient Light-Weight Few-Shot Keypoint Detector', in Proceedings of the Aaai Conference on Artificial Intelligence, pp. 3882 - 3890, http://dx.doi.org/10.1609/aaai.v38i4.28180

Shi W; Lu C; Shao M; Zhang Y; Xia S; Koniusz P, 2024, 'Few-shot Shape Recognition by Learning Deep Shape-aware Features', in Proceedings 2024 IEEE Winter Conference on Applications of Computer Vision Wacv 2024, pp. 1837 - 1848, http://dx.doi.org/10.1109/WACV57701.2024.00186

Zhang S; Ni Y; Du J; Liu Y; Koniusz P, 2024, 'Semantic Transfer from Head to Tail: Enlarging Tail Margin for Long-Tailed Visual Recognition', in Proceedings 2024 IEEE Winter Conference on Applications of Computer Vision Wacv 2024, pp. 1339 - 1349, http://dx.doi.org/10.1109/WACV57701.2024.00138

Dong J; Koniusz P; Chen J; Xie X; Ong YS, 2024, 'Adversarially Robust Few-shot Learning via Parameter Co-distillation of Similarity and Class Concept Learners', in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 28535 - 28544, http://dx.doi.org/10.1109/CVPR52733.2024.02696

Ni Y; Koniusz P, 2024, 'CHAIN: Enhancing Generalization in Data-Efficient GANs via LipsCHitz Continuity ConstrAIned Normalization', in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 6763 - 6774, http://dx.doi.org/10.1109/CVPR52733.2024.00646

Wang L; Koniusz P, 2024, 'FLOW DYNAMICS CORRECTION FOR ACTION RECOGNITION', in ICASSP IEEE International Conference on Acoustics Speech and Signal Processing Proceedings, pp. 3795 - 3799, http://dx.doi.org/10.1109/ICASSP48485.2024.10446223

Wang L; Sun K; Koniusz P, 2024, 'HIGH-ORDER TENSOR POOLING WITH ATTENTION FOR ACTION RECOGNITION', in ICASSP IEEE International Conference on Acoustics Speech and Signal Processing Proceedings, pp. 3885 - 3889, http://dx.doi.org/10.1109/ICASSP48485.2024.10446900

Chen Q; Wang L; Koniusz P; Gedeon T, 2024, 'Motion meets Attention: Video Motion Prompts', in Proceedings of Machine Learning Research, pp. 591 - 606

Ni Y; Zhang S; Koniusz P, 2024, 'PACE: Marrying generalization in PArameter-efficient fine-tuning with Consistency rEgularization', in Advances in Neural Information Processing Systems

Haghighat M; Moghadam P; Mohamed S; Koniusz P, 2024, 'PRE-TRAINING WITH RANDOM ORTHOGONAL PROJECTION IMAGE MODELING', in 12th International Conference on Learning Representations Iclr 2024

Dong J; Koniusz P; Chen J; Wang ZJ; Ong YS, 2024, 'Robust Distillation via Untargeted and Targeted Intermediate Adversarial Samples', in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 28432 - 28442, http://dx.doi.org/10.1109/CVPR52733.2024.02686

Zhang Y; Zhu H; Song Z; Koniusz P; King I, 2023, 'Spectral Feature Augmentation for Graph Contrastive Learning and Beyond', in Proceedings of the 37th Aaai Conference on Artificial Intelligence Aaai 2023, pp. 11289 - 11297, http://dx.doi.org/10.1609/aaai.v37i9.26336

Prabowo A; Shao W; Xue H; Koniusz P; Salim FD, 2023, 'Because Every Sensor Is Unique, so Is Every Pair: Handling Dynamicity in Traffic Forecasting', in ACM International Conference Proceeding Series, pp. 93 - 104, http://dx.doi.org/10.1145/3576842.3582362

Wang L; Koniusz P, 2023, '3Mformer: Multi-order Multi-mode Transformer for Skeletal Action Recognition', in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 5620 - 5631, http://dx.doi.org/10.1109/CVPR52729.2023.00544

Kang D; Koniusz P; Cho M; Murray N, 2023, 'Distilling Self-Supervised Vision Transformers for Weakly-Supervised Few-Shot Classification & Segmentation', in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 19627 - 19638, http://dx.doi.org/10.1109/CVPR52729.2023.01880

Zhang H; Torr PHS; Koniusz P, 2023, 'Improving Few-shot Learning by Spatially-aware Matching and CrossTransformer', in Lecture Notes in Computer Science, pp. 3 - 20, http://dx.doi.org/10.1007/978-3-031-26348-4_1

Rahman S; Koniusz P; Wang L; Zhou L; Moghadam P; Sun C, 2023, 'Learning Partial Correlation based Deep Visual Representation for Image Classification', in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 6231 - 6242, http://dx.doi.org/10.1109/CVPR52729.2023.00603

Zhang Z; Wang L; Zhou L; Koniusz P, 2023, 'Learning Spatial-context-aware Global Visual Feature Representation for Instance Image Retrieval', in Proceedings of the IEEE International Conference on Computer Vision, pp. 11216 - 11225, http://dx.doi.org/10.1109/ICCV51070.2023.01033

Zhang Y; Zhu H; Chen Y; Song Z; Koniusz P; King I, 2023, 'Mitigating the Popularity Bias of Graph Collaborative Filtering: A Dimensional Collapse Perspective', in Advances in Neural Information Processing Systems

Ni Y; Koniusz P, 2023, 'NICE: NoIse-modulated Consistency rEgularization for Data-Efficient GANs', in Advances in Neural Information Processing Systems

Wang L; Koniusz P, 2023, 'Temporal-Viewpoint Transportation Plan for Skeletal Few-Shot Action Recognition', in Lecture Notes in Computer Science, pp. 307 - 326, http://dx.doi.org/10.1007/978-3-031-26316-3_19

Zhu H; Koniusz P, 2023, 'Transductive Few-Shot Learning with Prototype-Based Label Propagation by Iterative Graph Refinement', in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 23996 - 24006, http://dx.doi.org/10.1109/CVPR52729.2023.02298

Zhang Y; Zhu H; Song Z; Koniusz P; King I, 2022, 'COSTA: Covariance-Preserving Feature Augmentation for Graph Contrastive Learning', in Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 2524 - 2534, http://dx.doi.org/10.1145/3534678.3539425

Zhang Y; Zhu H; Meng Z; Koniusz P; King I, 2022, 'Graph-adaptive Rectified Linear Unit for Graph Neural Networks', in Www 2022 Proceedings of the ACM Web Conference 2022, pp. 1331 - 1339, http://dx.doi.org/10.1145/3485447.3512159

Zhu H; Koniusz P, 2022, 'EASE: Unsupervised Discriminant Subspace Learning for Transductive Few-Shot Learning', in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 9068 - 9078, http://dx.doi.org/10.1109/CVPR52688.2022.00887

Lu C; Koniusz P, 2022, 'Few-shot Keypoint Detection with Uncertainty Learning for Unseen Species', in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 19394 - 19404, http://dx.doi.org/10.1109/CVPR52688.2022.01881

Zhu H; Koniusz P, 2022, 'Generalized Laplacian Eigenmaps', in Advances in Neural Information Processing Systems

Zhang S; Wang L; Murray N; Koniusz P, 2022, 'Kernelized Few-shot Object Detection with Efficient Integral Aggregation', in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 19185 - 19194, http://dx.doi.org/10.1109/CVPR52688.2022.01861

Ni Y; Koniusz P; Hartley R; Nock R, 2022, 'Manifold Learning Benefits GANs', in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 11255 - 11264, http://dx.doi.org/10.1109/CVPR52688.2022.01098

Simon C; Koniusz P; Harandi M, 2022, 'Meta-Learning for Multi-Label Few-Shot Classification', in Proceedings 2022 IEEE Cvf Winter Conference on Applications of Computer Vision Wacv 2022, pp. 346 - 355, http://dx.doi.org/10.1109/WACV51458.2022.00042

Song P; Zhang J; Koniusz P; Barnes N, 2022, 'MULTI-MODAL TRANSFORMER FOR RGB-D SALIENT OBJECT DETECTION', in Proceedings International Conference on Image Processing Icip, pp. 2466 - 2470, http://dx.doi.org/10.1109/ICIP46576.2022.9898069

Zhang S; Murray N; Wang L; Koniusz P, 2022, 'Time-rEversed DiffusioN tEnsor Transformer: A New TENET of Few-Shot Object Detection', in Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, pp. 310 - 328, http://dx.doi.org/10.1007/978-3-031-20044-1_18

Simon C; Koniusz P; Petersson L; Han Y; Harandi M, 2022, 'Towards a Robust Differentiable Architecture Search under Label Noise', in Proceedings 2022 IEEE Cvf Winter Conference on Applications of Computer Vision Wacv 2022, pp. 3584 - 3594, http://dx.doi.org/10.1109/WACV51458.2022.00364

Wang L; Koniusz P, 2022, 'Uncertainty-DTW for Time Series and Sequences', in Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, pp. 176 - 195, http://dx.doi.org/10.1007/978-3-031-19803-8_11

Zhu H; Koniusz P, 2021, 'REFINE: Random RangE FInder for Network Embedding', in International Conference on Information and Knowledge Management Proceedings, pp. 3682 - 3686, http://dx.doi.org/10.1145/3459637.3482168

Wang L; Koniusz P, 2021, 'Self-supervising Action Recognition by Statistical Moment and Subspace Descriptors', in Mm 2021 Proceedings of the 29th ACM International Conference on Multimedia, pp. 4324 - 4333, http://dx.doi.org/10.1145/3474085.3475572

Simon C; Koniusz P; Harandi M, 2021, 'On Learning the Geodesic Path for Incremental Learning', Institute of Electrical and Electronics Engineers (IEEE), pp. 1591 - 1600, presented at 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), http://dx.doi.org/10.1109/cvpr46437.2021.00164

Zhu H; Sun K; Koniusz P, 2021, 'Contrastive Laplacian Eigenmaps', in Advances in Neural Information Processing Systems, pp. 5682 - 5695

Zhang S; Luo D; Wang L; Koniusz P, 2021, 'Few-Shot Object Detection by Second-Order Pooling', in Lecture Notes in Computer Science, pp. 369 - 387, http://dx.doi.org/10.1007/978-3-030-69538-5_23

Zhang H; Koniusz P; Jian S; Li H; Torr PHS, 2021, 'Rethinking Class Relations: Absolute-relative Supervised and Unsupervised Few-shot Learning', in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 9427 - 9436, http://dx.doi.org/10.1109/CVPR46437.2021.00931

Tas Y; Koniusz P, 2021, 'Simple Dialogue System with AUDITED', in 32nd British Machine Vision Conference Bmvc 2021

Zhu H; Koniusz P, 2021, 'SIMPLE SPECTRAL GRAPH CONVOLUTION', in Iclr 2021 9th International Conference on Learning Representations, http://dx.doi.org/10.26190/unsworks/32608

Yu X; Zhuang Z; Koniusz P; Li H, 2020, '6DoF Object Pose Estimation via Differentiable Proxy Voting Regularizer', in 31st British Machine Vision Conference Bmvc 2020

Hou W; Suominen H; Koniusz P; Caldwell S; Gedeon T, 2020, 'A Token-Wise CNN-Based Method for Sentence Compression', in Lecture Notes in Computer Science, pp. 668 - 679, http://dx.doi.org/10.1007/978-3-030-63830-6_56

Simon C; Koniusz P; Nock R; Harandi M, 2020, 'Adaptive subspaces for few-shot learning', in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 4135 - 4144, http://dx.doi.org/10.1109/CVPR42600.2020.00419

Zhang H; Zhang L; Qi X; Li H; Torr PHS; Koniusz P, 2020, 'Few-Shot Action Recognition with Permutation-Invariant Attention', in Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, pp. 525 - 542, http://dx.doi.org/10.1007/978-3-030-58558-7_31

Simon C; Koniusz P; Nock R; Harandi M, 2020, 'On Modulating the Gradient for Meta-learning', in Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, pp. 556 - 572, http://dx.doi.org/10.1007/978-3-030-58598-3_33

Wang X; Salim FD; Ren Y; Koniusz P, 2020, 'Relation Embedding for Personalised Translation-Based POI Recommendation', in Lecture Notes in Computer Science, pp. 53 - 64, http://dx.doi.org/10.1007/978-3-030-47426-3_5

Prabowo A; Koniusz P; Shao W; Salim FD, 2019, 'COLTRANE: ConvolutiOnaL TRAjectory network for deep map inference', in Buildsys 2019 Proceedings of the 6th ACM International Conference on Systems for Energy Efficient Buildings Cities and Transportation, pp. 21 - 30, http://dx.doi.org/10.1145/3360322.3360853

Back to profile page