Tristan Laidlow
- Computer Vision and Pattern Recognition top 5%
- Aerospace Engineering top 10%
- Geology top 5%
- Computational Mechanics top 10%
- Computer Graphics and Computer-Aided Design top 5%
- Co-authors
- Stefan LeuteneggerAndrew J. DavisonShuaifeng ZhiJan CzarnowskiMichael BloeschWenbin LiStephen JamesKentaro Wada
- Topics
- Robotics and Sensor-Based Localization (8 papers)Advanced Vision and Imaging (5 papers)3D Surveying and Cultural Heritage (3 papers)
- Journals
- IEEE Robotics and Automation Letters2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)2021 IEEE/CVF International Conference on Computer Vision (ICCV)
- Partner nations
- United KingdomChina
In The Last Decade
Tristan Laidlow
8 papers receiving 361 citations
Hit Papers
Peers
Comparison fields: 5 of 39
- Computer Vision and Pattern Recognition 280
- Aerospace Engineering 146
- Geology 77
- Computational Mechanics 75
- Computer Graphics and Computer-Aided Design 69
Countries citing papers authored by Tristan Laidlow
This map shows the geographic impact of Tristan Laidlow'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 Tristan Laidlow with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tristan Laidlow more than expected).
Fields of papers citing papers by Tristan Laidlow
This network shows the impact of papers produced by Tristan Laidlow. 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 Tristan Laidlow. The network helps show where Tristan Laidlow may publish in the future.
Co-authorship network of co-authors of Tristan Laidlow
This figure shows the co-authorship network connecting the top 25 collaborators of Tristan Laidlow. A scholar is included among the top collaborators of Tristan Laidlow 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 Tristan Laidlow. Tristan Laidlow is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 18 | |
| 2 | 36 | |
| 3 | In-Place Scene Labelling and Understanding with Implicit Scene Representationbreakdown → | 212 |
| 4 | 2 | |
| 5 | 2 | |
| 6 | 13 | |
| 7 | 44 | |
| 8 | 43 |
About Tristan Laidlow
Tristan Laidlow is a scholar working on Geology, Computer Vision and Pattern Recognition and Aerospace Engineering, having authored 8 papers that have together received 370 indexed citations. Recurring topics across this work include Robotics and Sensor-Based Localization (8 papers), Advanced Vision and Imaging (5 papers) and 3D Surveying and Cultural Heritage (3 papers). The work is most often cited by research in Computer Graphics and Computer-Aided Design (69 citations), Geology (77 citations) and Computer Vision and Pattern Recognition (280 citations). Tristan Laidlow has collaborated with scholars based in United Kingdom and China. Frequent co-authors include Stefan Leutenegger, Andrew J. Davison, Shuaifeng Zhi, Jan Czarnowski, Michael Bloesch, Wenbin Li, Stephen James, Kentaro Wada, André Mouton and Ronald Clark. Their work appears in journals such as IEEE Robotics and Automation Letters, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 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.