Julian Straub

1.5k total citations
15 papers, 381 citations indexed

About

Julian Straub is a scholar working on Computer Vision and Pattern Recognition, Aerospace Engineering and Geology. According to data from OpenAlex, Julian Straub has authored 15 papers receiving a total of 381 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Computer Vision and Pattern Recognition, 11 papers in Aerospace Engineering and 4 papers in Geology. Recurrent topics in Julian Straub's work include Robotics and Sensor-Based Localization (11 papers), Advanced Vision and Imaging (6 papers) and Advanced Image and Video Retrieval Techniques (5 papers). Julian Straub is often cited by papers focused on Robotics and Sensor-Based Localization (11 papers), Advanced Vision and Imaging (6 papers) and Advanced Image and Video Retrieval Techniques (5 papers). Julian Straub collaborates with scholars based in United States, Israel and Australia. Julian Straub's co-authors include John W. Fisher, John J. Leonard, Oren Freifeld, Guy Rosman, Richard Newcombe, Steven Lovegrove, Georgia Gkioxari, Justin C. Johnson, Nikhila Ravi and Garrick Brazil and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, ACM Transactions on Graphics and 2021 IEEE/CVF International Conference on Computer Vision (ICCV).

In The Last Decade

Julian Straub

14 papers receiving 375 citations

Peers

Julian Straub
Jingwen Wang China
Visesh Chari India
Patrick Sayd France
Branislav Mičušík Austria
Liuyuan Deng China
Oliver Wasenmüller Germany
Siavash Zokai United States
Martin Lambers Germany
Jingwen Wang China
Julian Straub
Citations per year, relative to Julian Straub Julian Straub (= 1×) peers Jingwen Wang

Countries citing papers authored by Julian Straub

Since Specialization
Citations

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

Fields of papers citing papers by Julian Straub

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Julian Straub

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

All Works

15 of 15 papers shown
1.
Wu, Xiaoyang, Daniel DeTone, Tianwei Shen, et al.. (2025). Sonata: Self-Supervised Learning of Reliable Point Representations. 22193–22204.
2.
Brazil, Garrick, Abhinav Kumar, Julian Straub, et al.. (2023). Omni3D: A Large Benchmark and Model for 3D Object Detection in the Wild. 13154–13164. 40 indexed citations
3.
Sarlin, Paul-Edouard, Daniel DeTone, Tsun-Yi Yang, et al.. (2023). OrienterNet: Visual Localization in 2D Public Maps with Neural Matching. 21632–21642. 45 indexed citations
4.
Jiang, Huaizu, et al.. (2023). Pixel-Aligned Recurrent Queries for Multi-View 3D Object Detection. 18324–18334. 5 indexed citations
5.
Straub, Julian, Tianwei Shen, Tsun-Yi Yang, et al.. (2022). Nerfels: Renderable Neural Codes for Improved Camera Pose Estimation. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW). 5057–5066. 3 indexed citations
6.
Li, Kejie, Daniel DeTone, Steven Chen, et al.. (2021). ODAM: Object Detection, Association, and Mapping using Posed RGB Video. 2021 IEEE/CVF International Conference on Computer Vision (ICCV). 5978–5988. 14 indexed citations
7.
Rünz, Martin, Kejie Li, Meng Tang, et al.. (2020). FroDO: From Detections to 3D Objects. 14708–14717. 39 indexed citations
8.
Whelan, Thomas J., Michael Goesele, Steven Lovegrove, et al.. (2018). Reconstructing scenes with mirror and glass surfaces. ACM Transactions on Graphics. 37(4). 1–11. 37 indexed citations
9.
Straub, Julian, Oren Freifeld, Guy Rosman, John J. Leonard, & John W. Fisher. (2017). The Manhattan Frame Model—Manhattan World Inference in the Space of Surface Normals. IEEE Transactions on Pattern Analysis and Machine Intelligence. 40(1). 235–249. 54 indexed citations
10.
Straub, Julian, Jason S. Chang, Oren Freifeld, & John W. Fisher. (2015). A Dirichlet Process Mixture Model for Spherical Data. International Conference on Artificial Intelligence and Statistics. 930–938. 25 indexed citations
11.
Straub, Julian, et al.. (2015). Real-time manhattan world rotation estimation in 3D. 1913–1920. 28 indexed citations
12.
Straub, Julian, et al.. (2015). Semantically-Aware Aerial Reconstruction from Multi-modal Data. 2156–2164. 16 indexed citations
13.
Straub, Julian, Guy Rosman, Oren Freifeld, John J. Leonard, & John W. Fisher. (2014). A Mixture of Manhattan Frames: Beyond the Manhattan World. 3770–3777. 52 indexed citations
14.
Straub, Julian, et al.. (2014). Bayesian nonparametric modeling of driver behavior. 932–938. 7 indexed citations
15.
Roberts, Richard, et al.. (2012). Saliency detection and model-based tracking: a two part vision system for small robot navigation in forested environment. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 8387. 83870S–83870S. 16 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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2026