Maxim Tatarchenko

2.7k total citations · 3 hit papers
10 papers, 1.2k citations indexed

About

Maxim Tatarchenko is a scholar working on Computer Vision and Pattern Recognition, Computational Mechanics and Geology. According to data from OpenAlex, Maxim Tatarchenko has authored 10 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Computer Vision and Pattern Recognition, 5 papers in Computational Mechanics and 3 papers in Geology. Recurrent topics in Maxim Tatarchenko's work include 3D Shape Modeling and Analysis (5 papers), Advanced Vision and Imaging (3 papers) and 3D Surveying and Cultural Heritage (3 papers). Maxim Tatarchenko is often cited by papers focused on 3D Shape Modeling and Analysis (5 papers), Advanced Vision and Imaging (3 papers) and 3D Surveying and Cultural Heritage (3 papers). Maxim Tatarchenko collaborates with scholars based in Germany, United States and Netherlands. Maxim Tatarchenko's co-authors include Thomas Brox, Alexey Dosovitskiy, Vladlen Koltun, Qian-Yi Zhou, Jaesik Park, Stephan R. Richter, René Ranftl, Zhuwen Li, Jost Tobias Springenberg and Oier Mees and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, International Journal of Computer Vision and Computer Vision and Image Understanding.

In The Last Decade

Maxim Tatarchenko

10 papers receiving 1.2k 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.

Octree Generating Networks: Efficient Convolutional Architectures for High-resolution 3D Outputs

2017 417 citations Maxim Tatarchenko, Alexey Dosovitskiy et al. profile →
Tangent Convolutions for Dense Prediction in 3D

2018 364 citations Maxim Tatarchenko, Jaesik Park et al. FreiDok plus (Universitätsbibliothek Freiburg) profile →
What Do Single-View 3D Reconstruction Networks Learn?

2019 256 citations Maxim Tatarchenko, Stephan R. Richter et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Maxim Tatarchenko Germany	6	800	673	446	382	249	10	1.2k
Ali Osman Ulusoy Germany	11	862 1.1×	731 1.1×	616 1.4×	382 1.0×	341 1.4×	13	1.4k
Gernot Riegler Austria	9	836 1.0×	703 1.0×	547 1.2×	357 0.9×	318 1.3×	12	1.3k
Binh‐Son Hua Hong Kong	18	836 1.0×	750 1.1×	659 1.5×	343 0.9×	388 1.6×	40	1.5k
Yan‐Pei Cao China	17	622 0.8×	576 0.9×	317 0.7×	422 1.1×	125 0.5×	57	1.1k
Bin Fan China	13	680 0.8×	513 0.8×	563 1.3×	218 0.6×	324 1.3×	48	1.2k
Martin Bokeloh Germany	17	611 0.8×	766 1.1×	289 0.6×	469 1.2×	144 0.6×	29	1.2k
Qiangui Huang United States	7	537 0.7×	437 0.6×	445 1.0×	150 0.4×	311 1.2×	9	949
Wenxuan Wu China	6	823 1.0×	435 0.6×	617 1.4×	254 0.7×	435 1.7×	17	1.2k
Sagi Katz Israel	10	1.2k 1.5×	1.0k 1.5×	250 0.6×	862 2.3×	189 0.8×	12	1.7k
Ruihui Li China	12	570 0.7×	421 0.6×	276 0.6×	319 0.8×	170 0.7×	27	846

Countries citing papers authored by Maxim Tatarchenko

Since Specialization

Citations

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

Fields of papers citing papers by Maxim Tatarchenko

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Maxim Tatarchenko

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

All Works

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10 of 10 papers shown

1.

Çiçek, Özgün, et al.. (2025). Realistic Evaluation of Deep Active Learning for Image Classification and Semantic Segmentation. International Journal of Computer Vision. 133(7). 4294–4316. 1 indexed citations

2.

Tatarchenko, Maxim, et al.. (2024). Accurate Training Data for Occupancy Map Prediction in Automated Driving Using Evidence Theory. 5281–5290. 2 indexed citations

3.

Tatarchenko, Maxim, et al.. (2024). Image semantic segmentation of indoor scenes: A survey. Computer Vision and Image Understanding. 248. 104102–104102. 7 indexed citations

4.

Tatarchenko, Maxim, et al.. (2023). Histogram-based Deep Learning for Automotive Radar. 1 indexed citations

5.

Tatarchenko, Maxim, Stephan R. Richter, René Ranftl, et al.. (2019). What Do Single-View 3D Reconstruction Networks Learn?. 3400–3409. 256 indexed citations breakdown →

6.

Mees, Oier, Maxim Tatarchenko, Thomas Brox, & Wolfram Burgard. (2019). Self-supervised 3D Shape and Viewpoint Estimation from Single Images for Robotics. 6083–6089. 10 indexed citations

7.

Böhm, Anton, Maxim Tatarchenko, & Thorsten Falk. (2019). ISOO^V2 _DL - Semantic Instance Segmentation of Touching and Overlapping Objects. FreiDok plus (Universitätsbibliothek Freiburg). 343–347. 3 indexed citations

8.

Tatarchenko, Maxim, Jaesik Park, Vladlen Koltun, & Qian-Yi Zhou. (2018). Tangent Convolutions for Dense Prediction in 3D. FreiDok plus (Universitätsbibliothek Freiburg). 3887–3896. 364 indexed citations breakdown →

9.

Tatarchenko, Maxim, Alexey Dosovitskiy, & Thomas Brox. (2017). Octree Generating Networks: Efficient Convolutional Architectures for High-resolution 3D Outputs. 2107–2115. 417 indexed citations breakdown →

10.

Dosovitskiy, Alexey, Jost Tobias Springenberg, Maxim Tatarchenko, & Thomas Brox. (2016). Learning to Generate Chairs, Tables and Cars with Convolutional Networks. IEEE Transactions on Pattern Analysis and Machine Intelligence. 39(4). 1–1. 144 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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