Piotr Koniusz

4.4k total citations · 2 hit papers
67 papers, 2.2k citations indexed

About

Piotr Koniusz is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Aerospace Engineering. According to data from OpenAlex, Piotr Koniusz has authored 67 papers receiving a total of 2.2k indexed citations (citations by other indexed papers that have themselves been cited), including 48 papers in Computer Vision and Pattern Recognition, 38 papers in Artificial Intelligence and 6 papers in Aerospace Engineering. Recurrent topics in Piotr Koniusz's work include Domain Adaptation and Few-Shot Learning (27 papers), Human Pose and Action Recognition (16 papers) and Advanced Image and Video Retrieval Techniques (15 papers). Piotr Koniusz is often cited by papers focused on Domain Adaptation and Few-Shot Learning (27 papers), Human Pose and Action Recognition (16 papers) and Advanced Image and Video Retrieval Techniques (15 papers). Piotr Koniusz collaborates with scholars based in Australia, China and United Kingdom. Piotr Koniusz's co-authors include Hongguang Zhang, Hongdong Li, Yuchao Dai, Hongguang Zhang, Hao Zhu, Christian Simon, Richard Nock, Mehrtash Harandi, Lei Wang and Krystian Mikolajczyk and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Journal of Hazardous Materials and International Journal of Computer Vision.

In The Last Decade

Piotr Koniusz

60 papers receiving 2.1k citations

Hit Papers

Deep Stacked Hierarchical Multi-Patch Network for Image D... 2019 2026 2021 2023 2019 2020 100 200 300
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Deep Stacked Hierarchical Multi-Patch Network for Image Deblurring
    2019 398 citations Hongguang Zhang, Yuchao Dai et al. ANU Open Research (Australian National University) profile →
  2. Adaptive Subspaces for Few-Shot Learning
    2020 299 citations Piotr Koniusz et al. profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Piotr Koniusz Australia 25 1.6k 1.2k 370 192 136 67 2.2k
Thomas Mensink Netherlands 21 2.3k 1.4× 1.1k 0.9× 269 0.7× 87 0.5× 112 0.8× 49 2.8k
Guo-Sen Xie China 26 1.5k 0.9× 1.2k 1.0× 257 0.7× 272 1.4× 79 0.6× 78 2.2k
Weilin Huang China 24 2.6k 1.7× 840 0.7× 687 1.9× 129 0.7× 134 1.0× 47 3.1k
Yazhou Yao China 25 1.5k 0.9× 1.0k 0.8× 255 0.7× 178 0.9× 66 0.5× 96 2.0k
Shohreh Kasaei Iran 19 1.4k 0.9× 494 0.4× 313 0.8× 202 1.1× 176 1.3× 167 1.9k
Henghui Ding Singapore 29 1.8k 1.1× 922 0.8× 147 0.4× 127 0.7× 109 0.8× 78 2.3k
Takeru Miyato Japan 5 1.5k 1.0× 1.5k 1.3× 155 0.4× 217 1.1× 100 0.7× 8 2.5k
Daniel Keysers Germany 27 2.4k 1.5× 943 0.8× 342 0.9× 156 0.8× 80 0.6× 66 2.9k
Xinmei Tian China 26 2.1k 1.4× 1.3k 1.1× 221 0.6× 93 0.5× 350 2.6× 116 2.8k
Gan Sun China 24 892 0.6× 925 0.8× 119 0.3× 102 0.5× 112 0.8× 68 1.7k

Countries citing papers authored by Piotr Koniusz

Since Specialization
Citations

This map shows the geographic impact of Piotr Koniusz's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Piotr Koniusz with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Piotr Koniusz more than expected).

Fields of papers citing papers by Piotr Koniusz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Piotr Koniusz. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Piotr Koniusz. The network helps show where Piotr Koniusz may publish in the future.

Co-authorship network of co-authors of Piotr Koniusz

This figure shows the co-authorship network connecting the top 25 collaborators of Piotr Koniusz. A scholar is included among the top collaborators of Piotr Koniusz based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Piotr Koniusz. Piotr Koniusz is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
2.
Li, Guang, et al.. (2025). Beyond decoders: Learning prompt-aware features for few-shot object counting. Neurocomputing. 651. 130997–130997.
3.
4.
Koniusz, Piotr, et al.. (2024). Multivariate prototype representation for domain-generalized incremental learning. Computer Vision and Image Understanding. 249. 104215–104215.
5.
Anand, Gaurangi, Piotr Koniusz, Anupama Kumar, et al.. (2024). Graph neural networks-enhanced relation prediction for ecotoxicology (GRAPE). Journal of Hazardous Materials. 472. 134456–134456. 5 indexed citations
6.
Koniusz, Piotr, et al.. (2024). $\bigcirc\!\!\!\!\bigcirc$ CHAIN: Enhancing Generalization in Data-Efficient GANs via LipsCHitz Continuity ConstrAIned Normalization. ANU Open Research (Australian National University). 6763–6774. 4 indexed citations
7.
Zhang, Hongguang, Chun Liu, Jiandong Wang, et al.. (2024). Saliency-guided meta-hallucinator for few-shot learning. Science China Information Sciences. 67(10). 1 indexed citations
8.
Li, Zhibin, Piotr Koniusz, Lu Zhang, Dan Pagendam, & Peyman Moghadam. (2023). Exploiting Field Dependencies for Learning on Categorical Data. IEEE Transactions on Pattern Analysis and Machine Intelligence. 45(11). 1–14. 3 indexed citations
9.
Xue, Hao, et al.. (2023). Traffic forecasting on new roads using spatial contrastive pre-training (SCPT). Data Mining and Knowledge Discovery. 38(3). 913–937. 7 indexed citations
10.
11.
Zhang, Yifei, Hao Zhu, Zixing Song, Piotr Koniusz, & Irwin King. (2023). Spectral Feature Augmentation for Graph Contrastive Learning and Beyond. Proceedings of the AAAI Conference on Artificial Intelligence. 37(9). 11289–11297. 48 indexed citations
12.
Zhang, Hongguang, et al.. (2022). Event-guided Multi-patch Network with Self-supervision for Non-uniform Motion Deblurring. International Journal of Computer Vision. 131(2). 453–470. 14 indexed citations
13.
Wang, Lei & Piotr Koniusz. (2021). Self-supervising Action Recognition by Statistical Moment and Subspace Descriptors. arXiv (Cornell University). 4324–4333. 33 indexed citations
14.
Zhang, Hongguang, Li Zhang, Xiaojuan Qi, et al.. (2020). Few-shot Action Recognition via Improved Attention with Self-supervision. arXiv (Cornell University). 2 indexed citations
15.
Wang, Lei, Piotr Koniusz, & Du Q. Huynh. (2019). Hallucinating Bag-of-Words and Fisher Vector IDT terms for CNN-based Action Recognition.. arXiv (Cornell University). 4 indexed citations
16.
Zhang, Hongguang, Yuchao Dai, Hongdong Li, & Piotr Koniusz. (2019). Deep Stacked Hierarchical Multi-Patch Network for Image Deblurring. ANU Open Research (Australian National University). 5971–5979. 398 indexed citations breakdown →
17.
Zhang, Hongguang, Jing Zhang, & Piotr Koniusz. (2019). Few-Shot Learning via Saliency-Guided Hallucination of Samples. 2765–2774. 157 indexed citations
18.
Shao, Wei, et al.. (2019). Flight Delay Prediction using Airport Situational Awareness Map. RMIT Research Repository (RMIT University Library). 432–435. 16 indexed citations
19.
Yu, Xin, et al.. (2017). Face Destylization. 4 indexed citations
20.
Koniusz, Piotr & Anoop Cherian. (2016). Sparse Coding for Third-Order Super-Symmetric Tensor Descriptors with Application to Texture Recognition. 5395–5403. 18 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Thomas Mensink Breakdown of academic impact, for papers by Guo-Sen Xie Breakdown of academic impact, for papers by Weilin Huang Breakdown of academic impact, for papers by Yazhou Yao Breakdown of academic impact, for papers by Shohreh Kasaei Breakdown of academic impact, for papers by Henghui Ding Breakdown of academic impact, for papers by Takeru Miyato Breakdown of academic impact, for papers by Daniel Keysers Breakdown of academic impact, for papers by Xinmei Tian Breakdown of academic impact, for papers by Gan Sun
Rankless by CCL
2026