Stephen Lombardi

3.0k total citations · 2 hit papers
22 papers, 1.8k citations indexed

About

Stephen Lombardi is a scholar working on Computer Vision and Pattern Recognition, Computer Graphics and Computer-Aided Design and Computational Mechanics. According to data from OpenAlex, Stephen Lombardi has authored 22 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Computer Vision and Pattern Recognition, 12 papers in Computer Graphics and Computer-Aided Design and 9 papers in Computational Mechanics. Recurrent topics in Stephen Lombardi's work include Advanced Vision and Imaging (14 papers), Computer Graphics and Visualization Techniques (12 papers) and 3D Shape Modeling and Analysis (9 papers). Stephen Lombardi is often cited by papers focused on Advanced Vision and Imaging (14 papers), Computer Graphics and Visualization Techniques (12 papers) and 3D Shape Modeling and Analysis (9 papers). Stephen Lombardi collaborates with scholars based in United States, Israel and Switzerland. Stephen Lombardi's co-authors include Tomas Simon, Jason Saragih, Yaser Sheikh, Ko Nishino, Gabriel Schwartz, Louis Kratz, Andreas Lehrmann, Michael Zollhoefer, Shih-En Wei and Michael Zollhöfer and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, ACM Transactions on Graphics and International Journal of Computer Vision.

In The Last Decade

Stephen Lombardi

22 papers receiving 1.7k citations

Hit Papers

Neural volumes 2019 2026 2021 2023 2019 2022 100 200 300 400

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Stephen Lombardi United States 16 1.5k 734 701 201 124 22 1.8k
Graham Fyffe United States 18 1.4k 0.9× 731 1.0× 432 0.6× 170 0.8× 89 0.7× 41 1.6k
Koki Nagano United States 19 1.4k 0.9× 503 0.7× 531 0.8× 130 0.6× 104 0.8× 45 1.7k
Christian Richardt United Kingdom 18 1.5k 1.0× 477 0.6× 304 0.4× 199 1.0× 115 0.9× 60 1.7k
Forrester Cole United States 21 1.2k 0.8× 707 1.0× 712 1.0× 78 0.4× 135 1.1× 39 1.7k
Hans‐Peter Seidel Germany 24 1.2k 0.8× 1.1k 1.5× 957 1.4× 105 0.5× 170 1.4× 163 1.9k
Abhijeet Ghosh United States 27 1.7k 1.1× 1.0k 1.4× 610 0.9× 243 1.2× 56 0.5× 91 2.2k
Sunil Hadap United States 22 1.6k 1.0× 818 1.1× 417 0.6× 273 1.4× 118 1.0× 43 1.9k
Pieter Peers United States 31 1.9k 1.3× 1.4k 1.9× 790 1.1× 183 0.9× 98 0.8× 77 2.4k
Ricardo Martin-Brualla United States 15 1.5k 1.0× 861 1.2× 680 1.0× 82 0.4× 79 0.6× 23 1.8k
Sean Fanello United States 20 1.1k 0.7× 365 0.5× 399 0.6× 89 0.4× 130 1.0× 45 1.4k

Countries citing papers authored by Stephen Lombardi

Since Specialization
Citations

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

Fields of papers citing papers by Stephen Lombardi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Stephen Lombardi

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

All Works

20 of 20 papers shown
1.
Flynn, John T., Michael Broxton, Lucy Chai, et al.. (2024). Quark: Real-time, High-resolution, and General Neural View Synthesis. ACM Transactions on Graphics. 43(6). 1–20. 1 indexed citations
2.
Wang, Ziyan, Giljoo Nam, Stephen Lombardi, et al.. (2023). NeuWigs: A Neural Dynamic Model for Volumetric Hair Capture and Animation. 8641–8651. 10 indexed citations
3.
Li, Junxuan, Shunsuke Saito, Tomas Simon, et al.. (2023). MEGANE: Morphable Eyeglass and Avatar Network. 12769–12779. 9 indexed citations
4.
Tewari, Ayush, Justus Thies, Ben Mildenhall, et al.. (2022). Advances in Neural Rendering. Computer Graphics Forum. 41(2). 703–735. 203 indexed citations breakdown →
5.
Cao, Chen, Tomas Simon, Jin K. Kim, et al.. (2022). Authentic volumetric avatars from a phone scan. ACM Transactions on Graphics. 41(4). 1–19. 74 indexed citations
6.
Jourabloo, Amin, Fernando De la Torre, Jason Saragih, et al.. (2022). Robust Egocentric Photo-realistic Facial Expression Transfer for Virtual Reality. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 20291–20300. 9 indexed citations
7.
Raj, Amit, Michael Zollhöfer, Tomas Simon, et al.. (2021). Pixel-aligned Volumetric Avatars. 11728–11737. 35 indexed citations
8.
Lombardi, Stephen, Tomas Simon, Gabriel Schwartz, et al.. (2021). Mixture of volumetric primitives for efficient neural rendering. ACM Transactions on Graphics. 40(4). 1–13. 18 indexed citations
9.
Bi, Sai, Stephen Lombardi, Shunsuke Saito, et al.. (2021). Deep relightable appearance models for animatable faces. ACM Transactions on Graphics. 40(4). 1–15. 1 indexed citations
10.
Wang, Ziyan, Timur Bagautdinov, Stephen Lombardi, et al.. (2021). Learning Compositional Radiance Fields of Dynamic Human Heads. 5700–5709. 57 indexed citations
11.
Lombardi, Stephen, Tomas Simon, Gabriel Schwartz, et al.. (2021). Mixture of volumetric primitives for efficient neural rendering. ACM Transactions on Graphics. 40(4). 1–13. 150 indexed citations
12.
Bi, Sai, Stephen Lombardi, Shunsuke Saito, et al.. (2021). Deep relightable appearance models for animatable faces. ACM Transactions on Graphics. 40(4). 1–15. 49 indexed citations
13.
Schwartz, Gabriel, Shih-En Wei, Stephen Lombardi, et al.. (2020). The eyes have it. ACM Transactions on Graphics. 39(4). 38 indexed citations
14.
Lombardi, Stephen, Tomas Simon, Jason Saragih, et al.. (2019). Neural volumes. ACM Transactions on Graphics. 38(4). 1–14. 418 indexed citations breakdown →
15.
Wei, Shih-En, Jason Saragih, Tomas Simon, et al.. (2019). VR facial animation via multiview image translation. ACM Transactions on Graphics. 38(4). 1–16. 94 indexed citations
16.
Lombardi, Stephen, Jason Saragih, Tomas Simon, & Yaser Sheikh. (2018). Deep appearance models for face rendering. ACM Transactions on Graphics. 37(4). 1–13. 166 indexed citations
17.
Lombardi, Stephen & Ko Nishino. (2015). Reflectance and Illumination Recovery in the Wild. IEEE Transactions on Pattern Analysis and Machine Intelligence. 38(1). 129–141. 63 indexed citations
18.
Lombardi, Stephen & Ko Nishino. (2012). Single image multimaterial estimation. 238–245. 20 indexed citations
19.
Nishino, Ko, Louis Kratz, & Stephen Lombardi. (2011). Bayesian Defogging. International Journal of Computer Vision. 98(3). 263–278. 291 indexed citations
20.
Nishino, Ko & Stephen Lombardi. (2010). Directional statistics-based reflectance model for isotropic bidirectional reflectance distribution functions. Journal of the Optical Society of America A. 28(1). 8–8. 25 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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