Rareş Ambruş
- Computer Vision and Pattern Recognition top 2%
- Aerospace Engineering top 5%
- Geology top 5%
- Media Technology top 5%
- Environmental Engineering top 10%
- Co-authors
- Adrien GaidonVitor GuiziliniPatric JensfeltJohn FolkessonSebastian ClaiciDian ChenNils BoreKaterina Fragkiadaki
- Topics
- Robotics and Sensor-Based Localization (14 papers)Advanced Vision and Imaging (11 papers)Optical measurement and interference techniques (8 papers)
- Journals
- Robotics and Autonomous SystemsIEEE Robotics and Automation Letters2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
- Partner nations
- United StatesSwedenGermany
In The Last Decade
Rareş Ambruş
35 papers receiving 623 citations
Peers
Comparison fields: 5 of 56
- Computer Vision and Pattern Recognition 476
- Aerospace Engineering 262
- Geology 108
- Media Technology 89
- Environmental Engineering 77
Countries citing papers authored by Rareş Ambruş
This map shows the geographic impact of Rareş Ambruş'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 Rareş Ambruş with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rareş Ambruş more than expected).
Fields of papers citing papers by Rareş Ambruş
This network shows the impact of papers produced by Rareş Ambruş. 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 Rareş Ambruş. The network helps show where Rareş Ambruş may publish in the future.
Co-authorship network of co-authors of Rareş Ambruş
This figure shows the co-authorship network connecting the top 25 collaborators of Rareş Ambruş. A scholar is included among the top collaborators of Rareş Ambruş 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 Rareş Ambruş. Rareş Ambruş 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 | 0 | |
| 4 | 0 | |
| 5 | 2 | |
| 6 | 1 | |
| 7 | 4 | |
| 8 | 7 | |
| 9 | 17 | |
| 10 | 29 | |
| 11 | 3 | |
| 12 | 39 | |
| 13 | 32 | |
| 14 | Single-Shot Scene Reconstruction | 5 |
| 15 | 18 | |
| 16 | PackNet-SfM: 3D Packing for Self-Supervised Monocular Depth Estimation. | 10 |
| 17 | 2 | |
| 18 | 20 | |
| 19 | 1 | |
| 20 | Terrain Classification for Autonomous Robot Mobility : from Safety, Security Rescue Robotics to Planetary Exploration | 7 |
About Rareş Ambruş
Rareş Ambruş is a scholar working on Computer Vision and Pattern Recognition, Geology and Computer Graphics and Computer-Aided Design, having authored 39 papers that have together received 651 indexed citations. Recurring topics across this work include Robotics and Sensor-Based Localization (14 papers), Advanced Vision and Imaging (11 papers) and Optical measurement and interference techniques (8 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (476 citations), Geology (108 citations) and Aerospace Engineering (262 citations). Rareş Ambruş has collaborated with scholars based in United States, Sweden and Germany. Frequent co-authors include Adrien Gaidon, Vitor Guizilini, Patric Jensfelt, John Folkesson, Sebastian Claici, Dian Chen, Nils Bore, Katerina Fragkiadaki, Adam W. Harley and Zhaoyuan Fang. Their work appears in journals such as Robotics and Autonomous Systems, IEEE Robotics and Automation Letters and 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
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.