Tristan Laidlow

686 total citations · 1 hit paper
8 papers, 370 citations indexed

About

Tristan Laidlow is a scholar working on Computer Vision and Pattern Recognition, Aerospace Engineering and Geology. According to data from OpenAlex, Tristan Laidlow has authored 8 papers receiving a total of 370 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Computer Vision and Pattern Recognition, 8 papers in Aerospace Engineering and 3 papers in Geology. Recurrent topics in Tristan Laidlow's work include Robotics and Sensor-Based Localization (8 papers), Advanced Vision and Imaging (5 papers) and 3D Surveying and Cultural Heritage (3 papers). Tristan Laidlow is often cited by papers focused on Robotics and Sensor-Based Localization (8 papers), Advanced Vision and Imaging (5 papers) and 3D Surveying and Cultural Heritage (3 papers). Tristan Laidlow collaborates with scholars based in United Kingdom and China. Tristan Laidlow's 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 and has published in prestigious 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).

In The Last Decade

Tristan Laidlow

8 papers receiving 361 citations

Hit Papers

align trajectories sort by overperformance

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

In-Place Scene Labelling and Understanding with Implicit Scene Representation

2021 212 citations Shuaifeng Zhi, Tristan Laidlow et al. 2021 IEEE/CVF International Conference on Computer Vision (ICCV) profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Tristan Laidlow United Kingdom	6	280	146	77	75	69	8	370
Shuaifeng Zhi China	9	329 1.2×	142 1.0×	99 1.3×	129 1.7×	78 1.1×	26	487
Lingni Ma Netherlands	10	284 1.0×	194 1.3×	133 1.7×	88 1.2×	43 0.6×	17	386
Ignas Budvytis United Kingdom	13	382 1.4×	55 0.4×	31 0.4×	104 1.4×	60 0.9×	26	444
Lintao Zheng China	9	191 0.7×	93 0.6×	67 0.9×	100 1.3×	24 0.3×	15	267
Kwan-Yee Lin China	12	502 1.8×	83 0.6×	72 0.9×	144 1.9×	76 1.1×	18	598
Suryansh Kumar United States	11	248 0.9×	105 0.7×	46 0.6×	50 0.7×	67 1.0×	25	311
Feitong Tan Canada	8	555 2.0×	140 1.0×	134 1.7×	87 1.2×	78 1.1×	16	633
Linghao Chen China	6	262 0.9×	162 1.1×	59 0.8×	86 1.1×	59 0.9×	12	358
Jasna Maver Slovenia	5	290 1.0×	191 1.3×	77 1.0×	36 0.5×	36 0.5×	15	353
Hansheng Chen China	7	229 0.8×	128 0.9×	34 0.4×	53 0.7×	51 0.7×	11	317

Countries citing papers authored by Tristan Laidlow

Since Specialization

Citations

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

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Sort: Min cites: Since: Top N: Style:

8 of 8 papers shown

1.

Zhi, Shuaifeng, et al.. (2022). iLabel: Revealing Objects in Neural Fields. IEEE Robotics and Automation Letters. 8(2). 832–839. 18 indexed citations

2.

James, Stephen, Kentaro Wada, Tristan Laidlow, & Andrew J. Davison. (2022). Coarse-to-Fine Q-attention: Efficient Learning for Visual Robotic Manipulation via Discretisation. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 13729–13738. 36 indexed citations

3.

Laidlow, Tristan, et al.. (2021). SIMstack: A Generative Shape and Instance Model for Unordered Object Stacks. 2021 IEEE/CVF International Conference on Computer Vision (ICCV). 2 indexed citations

4.

Zhi, Shuaifeng, Tristan Laidlow, Stefan Leutenegger, & Andrew J. Davison. (2021). In-Place Scene Labelling and Understanding with Implicit Scene Representation. 2021 IEEE/CVF International Conference on Computer Vision (ICCV). 15818–15827. 212 indexed citations breakdown →

5.

Laidlow, Tristan, et al.. (2020). Towards the Probabilistic Fusion of Learned Priors into Standard Pipelines for 3D Reconstruction. Spiral (Imperial College London). 33. 7373–7379. 2 indexed citations

6.

Laidlow, Tristan, Jan Czarnowski, & Stefan Leutenegger. (2019). DeepFusion: Real-Time Dense 3D Reconstruction for Monocular SLAM using Single-View Depth and Gradient Predictions. Spiral (Imperial College London). 4068–4074. 44 indexed citations

7.

Bloesch, Michael, Tristan Laidlow, Ronald Clark, Stefan Leutenegger, & Andrew J. Davison. (2019). Learning Meshes for Dense Visual SLAM. Spiral (Imperial College London). 5854–5863. 13 indexed citations

8.

Laidlow, Tristan, Michael Bloesch, Wenbin Li, & Stefan Leutenegger. (2017). Dense RGB-D-inertial SLAM with map deformations. 6741–6748. 43 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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