Paul Newman

18.4k total citations · 7 hit papers
178 papers, 12.2k citations indexed

About

Paul Newman is a scholar working on Computer Vision and Pattern Recognition, Aerospace Engineering and Environmental Engineering. According to data from OpenAlex, Paul Newman has authored 178 papers receiving a total of 12.2k indexed citations (citations by other indexed papers that have themselves been cited), including 115 papers in Computer Vision and Pattern Recognition, 106 papers in Aerospace Engineering and 26 papers in Environmental Engineering. Recurrent topics in Paul Newman's work include Robotics and Sensor-Based Localization (103 papers), Advanced Image and Video Retrieval Techniques (40 papers) and Advanced Vision and Imaging (38 papers). Paul Newman is often cited by papers focused on Robotics and Sensor-Based Localization (103 papers), Advanced Image and Video Retrieval Techniques (40 papers) and Advanced Vision and Imaging (38 papers). Paul Newman collaborates with scholars based in United Kingdom, United States and Australia. Paul Newman's co-authors include Mark Cummins, John J. Leonard, Hugh Durrant‐Whyte, Gamini Dissanayake, S. Clark, Will Maddern, Geoffrey Pascoe, Winston Churchill, Ingmar Posner and José Neira and has published in prestigious journals such as SHILAP Revista de lepidopterología, Sensors and Journal of Accounting Research.

In The Last Decade

Paul Newman

172 papers receiving 11.5k citations

Hit Papers

5 papers align trajectories

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.

A solution to the simultaneous localization and map building (SLAM) problem

2001 1.9k citations Paul Newman et al. profile →
FAB-MAP: Probabilistic Localization and Mapping in the Space of Appearance

2008 1.0k citations Mark Cummins, Paul Newman The International Journal of Robotics Research profile →
1 year, 1000 km: The Oxford RobotCar dataset

2016 962 citations Will Maddern, Geoffrey Pascoe et al. The International Journal of Robotics Research profile →
Visual Place Recognition: A Survey

2015 692 citations Paul Newman, John J. Leonard et al. profile →
Appearance-only SLAM at large scale with FAB-MAP 2.0

2010 425 citations Mark Cummins, Paul Newman The International Journal of Robotics Research profile →
Robust Mapping and Localization in Indoor Environments Using Sonar Data

2002 393 citations Paul Newman, John J. Leonard et al. The International Journal of Robotics Research profile →
The Oxford Radar RobotCar Dataset: A Radar Extension to the Oxford RobotCar Dataset

2020 280 citations Dan Barnes, Matthew Gadd et al. profile →

Peers

Countries citing papers authored by Paul Newman

Since Specialization

Citations

This map shows the geographic impact of Paul Newman'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 Paul Newman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Paul Newman more than expected).

Fields of papers citing papers by Paul Newman

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Paul Newman. 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 Paul Newman. The network helps show where Paul Newman may publish in the future.

Co-authorship network of co-authors of Paul Newman

This figure shows the co-authorship network connecting the top 25 collaborators of Paul Newman. A scholar is included among the top collaborators of Paul Newman 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 Paul Newman. Paul Newman 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:

20 of 20 papers shown

#	Work	Indexed citations
1	OORD: The Oxford Offroad Radar Dataset 2024 ·IEEE Transactions on Intelligent Transportation Systems ·Matthew Gadd, Daniele De Martini, (unknown), Paul Murcutt, (unknown), (unknown), (unknown), Luke Robinson, (unknown), (unknown), (unknown), Letizia Marchegiani, Paul Newman, Lars Kunze	9
2	Point-based metric and topological localisation between lidar and overhead imagery 2023 ·Autonomous Robots ·(unknown), Daniele De Martini, Paul Newman	4
3	Self-Supervised Lidar Place Recognition in Overhead Imagery Using Unpaired Data 2023 ·(unknown), Daniele De Martini, Paul Newman	0
4	Self-supervised learning for using overhead imagery as maps in outdoor range sensor localization 2021 ·The International Journal of Robotics Research ·(unknown), Daniele De Martini, Shangzhe Wu, Paul Newman	22
5	The Oxford Radar RobotCar Dataset: A Radar Extension to the Oxford RobotCar Dataset breakdown → 2020 ·Dan Barnes, Matthew Gadd, Paul Murcutt, Paul Newman, Ingmar Posner	280
6	Reducing Steganography In Cycle-consistency GANs 2019 ·Computer Vision and Pattern Recognition ·(unknown), (unknown), Paul Newman	2
7	Fast Radar Motion Estimation with a Learnt Focus of Attention using Weak Supervision 2019 ·(unknown), Daniele De Martini, Matthew Gadd, Paul Newman	48
8	Depth-Map Improvement Via Architectural Priors 2018 ·(unknown), (unknown), Lina María Paz, Paul Newman	1
9	1 year, 1000 km: The Oxford RobotCar dataset breakdown → 2016 ·The International Journal of Robotics Research ·Will Maddern, Geoffrey Pascoe, (unknown), Paul Newman	962
10	From dusk till dawn: Localisation at night using artificial light sources 2015 ·Peter Nelson, Winston Churchill, Ingmar Posner, Paul Newman	24
11	Cross-calibration of push-broom 2D LIDARs and cameras in natural scenes 2013 ·(unknown), Peter Corke, Paul Newman	51
12	Cross-calbration of push-broom 2D LIDARs and cameras in natural scenes 2013 ·Science & Engineering Faculty ·(unknown), Peter Corke, Paul Newman	2
13	Self help: Seeking out perplexing images for ever improving navigation 2011 ·Rohan Paul, Paul Newman	6
14	Adaptive compression for 3D laser data 2011 ·The International Journal of Robotics Research ·Mike Smith, Ingmar Posner, Paul Newman	16
15	FAB-MAP: Appearance-Based Place Recognition and Mapping using a Learned Visual Vocabulary Model 2010 ·Oxford University Research Archive (ORA) (University of Oxford) ·Mark Cummins, Paul Newman	23
16	Performance Measure Aggregation, Career Incentives, and Explicit Incentives 2009 ·SSRN Electronic Journal ·(unknown), Shane S. Dikolli, Paul Newman	0
17	Data Papers - Peer Reviewed Publication of High Quality Data Sets 2009 ·The International Journal of Robotics Research ·Paul Newman, Peter Corke, (unknown)	4
18	A generative framework for fast urban labeling using spatial and temporal context 2009 ·Autonomous Robots ·Ingmar Posner, Mark Cummins, Paul Newman	47
19	Consistent, convergent, and constant-time SLAM 2003 ·Oxford University Research Archive (ORA) (University of Oxford) ·John J. Leonard, Paul Newman	85
20	On the Structure and Solution of the Simultaneous Localisation and Map Building Problem 1999 ·Paul Newman	132

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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