Jan Hosang
- Computer Vision and Pattern Recognition top 0.5%
- Artificial Intelligence top 2%
- Aerospace Engineering top 5%
- Automotive Engineering top 5%
- Media Technology top 2%
- Co-authors
- Rodrigo BenensonBernt SchieleMohamed OmranPiotr DollárMatthias HeinAnna KhorevaShanshan ZhangAndrea Tagliasacchi
- Topics
- Advanced Neural Network Applications (7 papers)Advanced Image and Video Retrieval Techniques (4 papers)Anomaly Detection Techniques and Applications (4 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceIEEE Transactions on Human-Machine Systems2021 IEEE/CVF International Conference on Computer Vision (ICCV)
- Partner nations
- GermanyUnited StatesCanada
In The Last Decade
Jan Hosang
10 papers receiving 2.3k citations
Hit Papers
Peers
Comparison fields: 5 of 119
- Computer Vision and Pattern Recognition 2.0k
- Artificial Intelligence 562
- Aerospace Engineering 324
- Automotive Engineering 195
- Media Technology 191
Countries citing papers authored by Jan Hosang
This map shows the geographic impact of Jan Hosang'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 Jan Hosang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jan Hosang more than expected).
Fields of papers citing papers by Jan Hosang
This network shows the impact of papers produced by Jan Hosang. 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 Jan Hosang. The network helps show where Jan Hosang may publish in the future.
Co-authorship network of co-authors of Jan Hosang
This figure shows the co-authorship network connecting the top 25 collaborators of Jan Hosang. A scholar is included among the top collaborators of Jan Hosang 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 Jan Hosang. Jan Hosang 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 | 169 | |
| 3 | Simple Does It: Weakly Supervised Instance and Semantic Segmentationbreakdown → | 468 |
| 4 | 137 | |
| 5 | Learning Non-maximum Suppressionbreakdown → | 438 |
| 6 | How Far are We from Solving Pedestrian Detection?breakdown → | 276 |
| 7 | 188 | |
| 8 | What Makes for Effective Detection Proposals?breakdown → | 495 |
| 9 | 138 | |
| 10 | 58 |
About Jan Hosang
Jan Hosang is a scholar working on Computer Vision and Pattern Recognition, Computer Graphics and Computer-Aided Design and Human-Computer Interaction, having authored 10 papers that have together received 2.4k indexed citations. Recurring topics across this work include Advanced Neural Network Applications (7 papers), Advanced Image and Video Retrieval Techniques (4 papers) and Anomaly Detection Techniques and Applications (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (2.0k citations), Media Technology (191 citations) and Artificial Intelligence (562 citations). Jan Hosang has collaborated with scholars based in Germany, United States and Canada. Frequent co-authors include Rodrigo Benenson, Bernt Schiele, Mohamed Omran, Piotr Dollár, Matthias Hein, Anna Khoreva, Shanshan Zhang, Andrea Tagliasacchi, Kwang Moo Yi and Eduard Trulls. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Human-Machine Systems and 2021 IEEE/CVF International Conference on Computer Vision (ICCV).
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.