Lars Mescheder

3.5k citations
8 papers · 632 · 1 hit paper · h-index 7

Impact in

Papers in

Lars Mescheder

8 papers receiving 610 citations

Lars Mescheder's Hit Papers

Augmented Reality Meets Computer Vision: Efficient Data Generation for Urban Driving Scenes 2018 · 277 citations
2770+2+5Years since publication50100150200250

Peers

Lars Mescheder
Comparison fields: 5 of 79
  • Computer Graphics and Computer-Aided Design 128
  • Computer Vision and Pattern Recognition 482
  • Computational Mechanics 147
  • Geology 32
  • Artificial Intelligence 135
Replace Pavel Tokmakov with:
Pavel Tokmakov United States
Eunbyung Park South Korea
Wenzhao Zheng China
Gengshan Yang United States
Holger Caesar Netherlands
Yuchi Huo China
Liangchen Song United States
Haiyu Zhao Singapore
Vincent Casser United States
Lars Mescheder relative to Pavel Tokmakov United States Pavel Tokmakov's profile →
Citations per field
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Citations per year

Countries citing papers authored by Lars Mescheder

Since Specialization
Citations

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

Fields of papers citing papers by Lars Mescheder

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 10 scholars most cited alongside Lars Mescheder, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Lars Mescheder Line = papers co-authored together Lars Mescheder links everyone, so they are left out of the graph.

All Works

8 of 8 papers shown

About Lars Mescheder

Lars Mescheder is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Statistical and Nonlinear Physics, Computer Graphics and Computer-Aided Design and Computational Mechanics, having authored 8 papers that have together received 632 indexed citations. Recurring topics across this work include Generative Adversarial Networks and Image Synthesis (4 papers), Advanced Vision and Imaging (2 papers), Model Reduction and Neural Networks (2 papers), Computer Graphics and Visualization Techniques (2 papers), Artificial Intelligence in Games (1 paper), Domain Adaptation and Few-Shot Learning (1 paper), Medical Image Segmentation Techniques (1 paper) and Image and Signal Denoising Methods (1 paper). The work is most often cited by research in Computer Graphics and Computer-Aided Design (128 citations), Computer Vision and Pattern Recognition (482 citations), Computational Mechanics (147 citations), Geology (32 citations) and Artificial Intelligence (135 citations). Lars Mescheder has collaborated with scholars based in Germany, Switzerland and India. Frequent co-authors include Andreas Geiger, Carsten Rother, Siva Karthik Mustikovela, Hassan Abu Alhaija, Sebastian Nowozin, Michael Oechsle, Michael Niemeyer, Katja Schwarz, Yiyi Liao and Dirk A. Lorenz. Their work appears in journals such as International Journal of Computer Vision, Journal of Mathematical Imaging and Vision, arXiv (Cornell University) and MPG.PuRe (Max Planck Society).

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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