Zsolt Kira

5.4k total citations
68 papers, 1.9k citations indexed

About

Zsolt Kira is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Aerospace Engineering. According to data from OpenAlex, Zsolt Kira has authored 68 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 45 papers in Computer Vision and Pattern Recognition, 40 papers in Artificial Intelligence and 11 papers in Aerospace Engineering. Recurrent topics in Zsolt Kira's work include Domain Adaptation and Few-Shot Learning (23 papers), Multimodal Machine Learning Applications (22 papers) and Advanced Neural Network Applications (15 papers). Zsolt Kira is often cited by papers focused on Domain Adaptation and Few-Shot Learning (23 papers), Multimodal Machine Learning Applications (22 papers) and Advanced Neural Network Applications (15 papers). Zsolt Kira collaborates with scholars based in United States, Slovakia and United Kingdom. Zsolt Kira's co-authors include Chih‐Yao Ma, Ghassan AlRegib, Yen‐Cheng Liu, Chia-Wen Kuo, Junjiao Tian, Min-Hung Chen, Jingdao Chen, Yong K. Cho, James Smith and Yen-Chang Hsu and has published in prestigious journals such as SAE technical papers on CD-ROM/SAE technical paper series, IEEE Robotics and Automation Letters and Journal of Computing in Civil Engineering.

In The Last Decade

Zsolt Kira

62 papers receiving 1.8k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Zsolt Kira United States 22 1.2k 765 245 158 151 68 1.9k
Henrik Kretzschmar Germany 15 842 0.7× 311 0.4× 315 1.3× 200 1.3× 78 0.5× 26 1.4k
Hongkai Yu United States 22 1.3k 1.1× 438 0.6× 196 0.8× 131 0.8× 39 0.3× 85 1.9k
Igor Gilitschenski United States 22 695 0.6× 486 0.6× 688 2.8× 212 1.3× 125 0.8× 86 1.6k
Jinshi Cui China 18 836 0.7× 349 0.5× 221 0.9× 74 0.5× 55 0.4× 63 1.2k
Min Sun United States 21 1.6k 1.3× 565 0.7× 326 1.3× 61 0.4× 63 0.4× 86 2.0k
Junfeng Fan China 27 771 0.6× 416 0.5× 268 1.1× 216 1.4× 146 1.0× 111 2.2k
Yuenan Hou China 16 856 0.7× 319 0.4× 232 0.9× 65 0.4× 149 1.0× 27 1.4k
Joanna Materzyńska Mexico 6 2.0k 1.6× 1.1k 1.4× 182 0.7× 89 0.6× 72 0.5× 6 2.3k
Akif Durdu Türkiye 20 417 0.3× 358 0.5× 304 1.2× 248 1.6× 49 0.3× 92 1.4k
Di Feng Germany 10 738 0.6× 325 0.4× 267 1.1× 131 0.8× 40 0.3× 10 1.3k

Countries citing papers authored by Zsolt Kira

Since Specialization
Citations

This map shows the geographic impact of Zsolt Kira'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 Zsolt Kira with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Zsolt Kira more than expected).

Fields of papers citing papers by Zsolt Kira

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Zsolt Kira. 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 Zsolt Kira. The network helps show where Zsolt Kira may publish in the future.

Co-authorship network of co-authors of Zsolt Kira

This figure shows the co-authorship network connecting the top 25 collaborators of Zsolt Kira. A scholar is included among the top collaborators of Zsolt Kira 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 Zsolt Kira. Zsolt Kira 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.
Chhablani, Gunjan, Théophile Gervet, Zsolt Kira, et al.. (2024). GOAT-Bench: A Benchmark for Multi-Modal Lifelong Navigation. 16373–16383. 1 indexed citations
2.
Kuo, Chia-Wen & Zsolt Kira. (2023). HAAV: Hierarchical Aggregation of Augmented Views for Image Captioning. 11039–11049. 26 indexed citations
3.
Liu, Yen‐Cheng, Chih‐Yao Ma, & Zsolt Kira. (2022). Unbiased Teacher v2: Semi-supervised Object Detection for Anchor-free and Anchor-based Detectors. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 9809–9818. 81 indexed citations
4.
Kuo, Chia-Wen & Zsolt Kira. (2022). Beyond a Pre-Trained Object Detector: Cross-Modal Textual and Visual Context for Image Captioning. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 17948–17958. 55 indexed citations
5.
Smith, James, et al.. (2021). Memory-Efficient Semi-Supervised Continual Learning: The World is its Own Replay Buffer. 1–8. 17 indexed citations
6.
Liu, Weiyu, et al.. (2020). Path Ranking with Attention to Type Hierarchies. Proceedings of the AAAI Conference on Artificial Intelligence. 34(3). 2893–2900. 7 indexed citations
7.
Liu, Yen‐Cheng, et al.. (2020). When2com: Multi-Agent Perception via Communication Graph Grouping. 4105–4114. 139 indexed citations
8.
Liu, Yen‐Cheng, et al.. (2020). Who2com: Collaborative Perception via Learnable Handshake Communication. 6876–6883. 100 indexed citations
9.
Ma, Chih‐Yao, Jiasen Lu, Zuxuan Wu, et al.. (2019). Self-Monitoring Navigation Agent via Auxiliary Progress Estimation. arXiv (Cornell University). 26 indexed citations
10.
Hsu, Yen-Chang, Zhaoyang Lv, & Zsolt Kira. (2017). Learning to cluster in order to transfer across domains and tasks. arXiv (Cornell University). 17 indexed citations
11.
Abernethy, Jacob, et al.. (2017). How to Train Your DRAGAN. arXiv (Cornell University). 12 indexed citations
12.
Kira, Zsolt, et al.. (2016). Fusing LIDAR and images for pedestrian detection using convolutional neural networks. 2198–2205. 101 indexed citations
13.
Carlone, Luca, et al.. (2014). Eliminating conditionally independent sets in factor graphs: A unifying perspective based on smart factors. SMARTech Repository (Georgia Institute of Technology). 4290–4297. 57 indexed citations
14.
Carlone, Luca, Pablo F. Alcantarilla, Han-Pang Chiu, Zsolt Kira, & Frank Dellaert. (2014). Mining Structure Fragments for Smart Bundle Adjustment. 3.1–3.12. 8 indexed citations
15.
Kira, Zsolt, et al.. (2012). Long-Range Pedestrian Detection using stereo and a cascade of convolutional network classifiers. 2396–2403. 7 indexed citations
16.
Kira, Zsolt. (2010). Inter-robot transfer learning for perceptual classification. Adaptive Agents and Multi-Agents Systems. 13–20. 11 indexed citations
17.
Kira, Zsolt, Ronald C. Arkin, & Thomas Collins. (2010). A design process for robot capabilities and missions applied to micro-autonomous platforms. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 7679. 767911–767911. 1 indexed citations
18.
Ulam, Patrick, Zsolt Kira, Ronald C. Arkin, & Thomas Collins. (2010). Mission specification and control for unmanned aerial and ground vehicles for indoor target discovery and tracking. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 7694. 769414–769414. 6 indexed citations
19.
Kira, Zsolt. (2009). Mapping Grounded Object Properties Across Perceptually Heterogeneous Embodiments. SMARTech Repository (Georgia Institute of Technology). 4 indexed citations
20.
Kira, Zsolt & Alan C. Schultz. (2006). Continuous and Embedded Learning for Multi-Agent Systems. 3184–3190. 5 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.

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