James Diebel

6.5k total citations · 2 hit papers
7 papers, 2.9k citations indexed

About

James Diebel is a scholar working on Computer Vision and Pattern Recognition, Aerospace Engineering and Computer Graphics and Computer-Aided Design. According to data from OpenAlex, James Diebel has authored 7 papers receiving a total of 2.9k indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Computer Vision and Pattern Recognition, 3 papers in Aerospace Engineering and 3 papers in Computer Graphics and Computer-Aided Design. Recurrent topics in James Diebel's work include Advanced Vision and Imaging (4 papers), Robotics and Sensor-Based Localization (3 papers) and Computer Graphics and Visualization Techniques (2 papers). James Diebel is often cited by papers focused on Advanced Vision and Imaging (4 papers), Robotics and Sensor-Based Localization (3 papers) and Computer Graphics and Visualization Techniques (2 papers). James Diebel collaborates with scholars based in United States, Netherlands and Switzerland. James Diebel's co-authors include Sebastian Thrun, Brian Curless, Daniel Scharstein, Steven M. Seitz, Richard Szeliski, Dmitri Dolgov, Michael Montemerlo, Michael Brünig, Jana Košecká and Young‐Min Kim and has published in prestigious journals such as ACM Transactions on Graphics, The International Journal of Robotics Research and Neural Information Processing Systems.

In The Last Decade

James Diebel

7 papers receiving 2.8k citations

Hit 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 Comparison and Evaluation of Multi-View Stereo Reconstruction Algorithms

2006 1.6k citations Steven M. Seitz, Brian Curless et al. profile →
Path Planning for Autonomous Vehicles in Unknown Semi-structured Environments

2010 660 citations Dmitri Dolgov, Sebastian Thrun et al. The International Journal of Robotics Research profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
James Diebel United States	7	2.3k	893	542	397	346	7	2.9k
Xinge Zhu China	21	2.1k 0.9×	838 0.9×	361 0.7×	116 0.3×	173 0.5×	42	2.9k
Jaesik Park South Korea	22	3.2k 1.4×	1.1k 1.3×	968 1.8×	540 1.4×	739 2.1×	58	4.3k
Gim Hee Lee Singapore	30	2.2k 1.0×	2.0k 2.2×	978 1.8×	217 0.5×	132 0.4×	88	3.6k
Xiaozhi Chen China	17	3.6k 1.5×	1.8k 2.0×	539 1.0×	93 0.2×	210 0.6×	48	4.6k
Michael Bosse Australia	31	3.2k 1.4×	3.4k 3.8×	1.3k 2.3×	442 1.1×	144 0.4×	52	4.9k
Haoqiang Fan China	21	2.9k 1.3×	621 0.7×	493 0.9×	558 1.4×	472 1.4×	39	3.9k
Xiaoyong Shen China	26	3.5k 1.5×	640 0.7×	277 0.5×	142 0.4×	765 2.2×	43	3.9k
Yongming Rao China	29	2.4k 1.0×	229 0.3×	556 1.0×	346 0.9×	325 0.9×	49	3.4k

Countries citing papers authored by James Diebel

Since Specialization

Citations

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

Fields of papers citing papers by James Diebel

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of James Diebel

This figure shows the co-authorship network connecting the top 25 collaborators of James Diebel. A scholar is included among the top collaborators of James Diebel 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 James Diebel. James Diebel is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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7 of 7 papers shown

1.

Dolgov, Dmitri, Sebastian Thrun, Michael Montemerlo, & James Diebel. (2010). Path Planning for Autonomous Vehicles in Unknown Semi-structured Environments. The International Journal of Robotics Research. 29(5). 485–501. 660 indexed citations breakdown →

2.

Kim, Young‐Min, et al.. (2009). Multi-view image and ToF sensor fusion for dense 3D reconstruction. 1542–1549. 94 indexed citations

3.

Thrun, Sebastian & James Diebel. (2008). Bayesian image vectorization: the probabilistic inversion of vector image rasterization. 216–216. 9 indexed citations

4.

Diebel, James, Sebastian Thrun, & Michael Brünig. (2006). A Bayesian method for probable surface reconstruction and decimation. ACM Transactions on Graphics. 25(1). 39–59. 77 indexed citations

5.

Seitz, Steven M., Brian Curless, James Diebel, Daniel Scharstein, & Richard Szeliski. (2006). A Comparison and Evaluation of Multi-View Stereo Reconstruction Algorithms. 1. 519–528. 1619 indexed citations breakdown →

6.

Diebel, James & Sebastian Thrun. (2005). An Application of Markov Random Fields to Range Sensing. Neural Information Processing Systems. 18. 291–298. 378 indexed citations

7.

Diebel, James, et al.. (2005). Simultaneous localization and mapping with active stereo vision. 4. 3436–3443. 33 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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