Aljoša Ošep

956 total citations
21 papers, 393 citations indexed

About

Aljoša Ošep is a scholar working on Computer Vision and Pattern Recognition, Aerospace Engineering and Environmental Engineering. According to data from OpenAlex, Aljoša Ošep has authored 21 papers receiving a total of 393 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Computer Vision and Pattern Recognition, 10 papers in Aerospace Engineering and 5 papers in Environmental Engineering. Recurrent topics in Aljoša Ošep's work include Video Surveillance and Tracking Methods (10 papers), Robotics and Sensor-Based Localization (10 papers) and Advanced Vision and Imaging (6 papers). Aljoša Ošep is often cited by papers focused on Video Surveillance and Tracking Methods (10 papers), Robotics and Sensor-Based Localization (10 papers) and Advanced Vision and Imaging (6 papers). Aljoša Ošep collaborates with scholars based in Germany, United States and Italy. Aljoša Ošep's co-authors include Laura Leal-Taixé, Bastian Leibe, Alexander Kim, Markus Mathias, Jörg Stückler, Deva Ramanan, Jonathon Luiten, Francis Engelmann, Alexander Hermans and Mengtian Li and has published in prestigious journals such as International Journal of Computer Vision, IEEE Robotics and Automation Letters and 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

In The Last Decade

Aljoša Ošep

19 papers receiving 374 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Aljoša Ošep Germany	9	300	152	95	64	60	21	393
Jae Shin Yoon United States	8	330 1.1×	119 0.8×	78 0.8×	40 0.6×	36 0.6×	16	424
Qingqiu Huang China	4	480 1.6×	225 1.5×	62 0.7×	61 1.0×	94 1.6×	6	612
Tongyi Cao Hong Kong	6	234 0.8×	99 0.7×	129 1.4×	65 1.0×	54 0.9×	9	359
Émilie Wirbel France	7	347 1.2×	112 0.7×	54 0.6×	68 1.1×	93 1.6×	12	439
Daiyi Peng United States	3	238 0.8×	129 0.8×	42 0.4×	54 0.8×	56 0.9×	5	322
Jianhui Liu China	6	300 1.0×	134 0.9×	37 0.4×	84 1.3×	38 0.6×	18	424
Guodong Xu China	7	308 1.0×	114 0.8×	40 0.4×	32 0.5×	79 1.3×	12	390
Jintao Xu China	9	173 0.6×	144 0.9×	81 0.9×	58 0.9×	23 0.4×	17	315
Inwook Shim South Korea	10	187 0.6×	115 0.8×	56 0.6×	46 0.7×	33 0.6×	29	301
Anshul Paigwar France	8	118 0.4×	86 0.6×	62 0.7×	84 1.3×	21 0.3×	15	252

Countries citing papers authored by Aljoša Ošep

Since Specialization

Citations

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

Fields of papers citing papers by Aljoša Ošep

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Aljoša Ošep

This figure shows the co-authorship network connecting the top 25 collaborators of Aljoša Ošep. A scholar is included among the top collaborators of Aljoša Ošep 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 Aljoša Ošep. Aljoša Ošep 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

Zhang, Yushan, Aljoša Ošep, Laura Leal-Taixé, & Tim Meinhardt. (2025). Zero-Shot 4D Lidar Panoptic Segmentation. 24506–24517. 1 indexed citations

Hu, Peiyun, et al.. (2024). Lidar Panoptic Segmentation in an Open World. International Journal of Computer Vision. 133(3). 1153–1174.

Ošep, Aljoša, et al.. (2024). SeMoLi: What Moves Together Belongs Together. 14685–14694.

Ferroni, Francesco, et al.. (2023). Pix2Map: Cross-Modal Retrieval for Inferring Street Maps from Images. 17514–17523. 4 indexed citations

Saltori, Cristiano, Aljoša Ošep, Elisa Ricci, & Laura Leal-Taixé. (2023). Walking Your LiDOG: A Journey Through Multiple Domains for LiDAR Semantic Segmentation. 196–206. 5 indexed citations

Agarwalla, Abhinav, Xuhua Huang, Jason Ziglar, et al.. (2023). Lidar Panoptic Segmentation and Tracking without Bells and Whistles. 3 indexed citations

Luiten, Jonathon, et al.. (2022). Forecasting from LiDAR via Future Object Detection. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 17181–17190. 22 indexed citations

Zhou, Qunjie, et al.. (2022). Text2Pos: Text-to-Point-Cloud Cross-Modal Localization. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 6677–6686. 9 indexed citations

Liu, Yang, Jonathon Luiten, Achal Dave, et al.. (2022). Opening up Open World Tracking. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 19023–19033. 27 indexed citations

10.

Demmel, Nikolaus, et al.. (2022). DirectTracker: 3D Multi-Object Tracking Using Direct Image Alignment and Photometric Bundle Adjustment. 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). 2 indexed citations

11.

Nunes, Lucas, Xieyuanli Chen, Aljoša Ošep, et al.. (2022). Unsupervised Class-Agnostic Instance Segmentation of 3D LiDAR Data for Autonomous Vehicles. IEEE Robotics and Automation Letters. 7(4). 8713–8720. 10 indexed citations

12.

Kim, Alexander, Aljoša Ošep, & Laura Leal-Taixé. (2021). EagerMOT: 3D Multi-Object Tracking via Sensor Fusion. 11315–11321. 128 indexed citations

13.

Ošep, Aljoša, et al.. (2021). A Single-Stage, Bottom-up Approach for Occluded VIS using Spatio-temporal Embeddings. 3851–3855. 2 indexed citations

14.

Ošep, Aljoša, et al.. (2020). Making a Case for 3D Convolutions for Object Segmentation in Videos. arXiv (Cornell University). 2 indexed citations

15.

Ošep, Aljoša, et al.. (2019). AlignNet-3D: Fast Point Cloud Registration of Partially Observed Objects. 29 indexed citations

16.

Ošep, Aljoša, et al.. (2017). Combined image- and world-space tracking in traffic scenes. 1988–1995. 78 indexed citations

17.

Ošep, Aljoša, et al.. (2016). Multi-scale object candidates for generic object tracking in street scenes. 27 indexed citations

18.

Ošep, Aljoša, et al.. (2016). Scene flow propagation for semantic mapping and object discovery in dynamic street scenes. OPUS (Augsburg University). 1785–1792. 39 indexed citations

19.

Ošep, Aljoša, et al.. (2016). Unsupervised Learning of Shape-Motion Patterns for Objects in Urban Street Scenes. 68.1–68.12. 2 indexed citations

20.

Mitzel, Dennis, et al.. (2015). A fixed-dimensional 3D shape representation for matching partially observed objects in street scenes. 1336–1343. 1 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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