Adam Kortylewski
- Computer Vision and Pattern Recognition top 2%
- Artificial Intelligence top 5%
- Computational Mechanics top 10%
- Aerospace Engineering
- Media Technology top 10%
- Topics
- Human Pose and Action Recognition (9 papers)Advanced Neural Network Applications (8 papers)Domain Adaptation and Few-Shot Learning (8 papers)
- Cited by
- Computer Vision and Pattern RecognitionComputer Graphics and Computer-Aided DesignArtificial Intelligence
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceACM Transactions on GraphicsInternational Journal of Computer Vision
- Partner nations
- United StatesGermanyChina
In The Last Decade
Adam Kortylewski
31 papers receiving 848 citations
Hit Papers
Peers
Comparison fields: 5 of 107
- Computer Vision and Pattern Recognition 632
- Artificial Intelligence 264
- Computational Mechanics 67
- Aerospace Engineering 52
- Media Technology 43
Countries citing papers authored by Adam Kortylewski
This map shows the geographic impact of Adam Kortylewski'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 Adam Kortylewski with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Adam Kortylewski more than expected).
Fields of papers citing papers by Adam Kortylewski
This network shows the impact of papers produced by Adam Kortylewski. 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 Adam Kortylewski. The network helps show where Adam Kortylewski may publish in the future.
Co-authorship network of co-authors of Adam Kortylewski
This figure shows the co-authorship network connecting the top 25 collaborators of Adam Kortylewski. A scholar is included among the top collaborators of Adam Kortylewski 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 Adam Kortylewski. Adam Kortylewski is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 1 | |
| 3 | 23 | |
| 4 | 0 | |
| 5 | 1 | |
| 6 | 11 | |
| 7 | 23 | |
| 8 | 10 | |
| 9 | 61 | |
| 10 | 16 | |
| 11 | 21 | |
| 12 | 13 | |
| 13 | TransFG: A Transformer Architecture for Fine-Grained Recognitionbreakdown → | 270 |
| 14 | 29 | |
| 15 | 18 | |
| 16 | 16 | |
| 17 | 1 | |
| 18 | NeMo: Neural Mesh Models of Contrastive Features for Robust 3D Pose Estimation | 1 |
| 19 | 60 | |
| 20 | Compositional Convolutional Networks For Robust Object Classification under Occlusion. | 2 |
About Adam Kortylewski
Adam Kortylewski is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Computational Mechanics, having authored 32 papers that have together received 869 indexed citations. Recurring topics across this work include Human Pose and Action Recognition (9 papers), Advanced Neural Network Applications (8 papers) and Domain Adaptation and Few-Shot Learning (8 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (632 citations), Computer Graphics and Computer-Aided Design (32 citations) and Artificial Intelligence (264 citations). Adam Kortylewski has collaborated with scholars based in United States, Germany and China. Frequent co-authors include Alan Yuille, Ju He, Yutong Bai, Changhu Wang, Shuai Liu, Jie-Neng Chen, Cheng Yang, Thomas Vetter, Angtian Wang and Bernhard Egger. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, ACM Transactions on Graphics and International Journal of Computer Vision.
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.