World's Best Scientists 2026 revealed!
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Computer Science
Germany
2026

D-Index & Metrics

Computer Science

D-Index
143
Citations
99982
World Ranking
52
National Ranking
4

Research.com Recognitions

  • 2026 - Research.com Computer Science in Germany Leader Award
  • 2025 - Research.com Computer Science in Germany Leader Award
  • 2023 - Research.com Computer Science in Germany Leader Award
  • 2022 - Research.com Computer Science in Germany Leader Award
  • 2021 - German National Academy of Sciences Leopoldina - Deutsche Akademie der Naturforscher Leopoldina – Nationale Akademie der Wissenschaften Informatics
  • 2018 - Fellow of the International Association for Pattern Recognition (IAPR) For contributions to large-scale object recognition, human detection and pose estimation
  • 2017 - IEEE Fellow For contributions to large-scale object recognition, human detection and pose estimation

Overview

Bernt Schiele is affiliated with the Max Planck Institute for Informatics in Germany, specializing in Computer Science with a predominant focus on Computer Vision and Pattern Recognition as well as Artificial Intelligence. Their research contributions extensively cover areas including Domain Adaptation and Few-Shot Learning, Advanced Neural Network Applications, and Multimodal Machine Learning Applications.

The scientist has contributed to various specialized subfields, such as:

  • Computer Vision and Pattern Recognition
  • Artificial Intelligence
  • Radiology, Nuclear Medicine and Imaging
  • Electrical and Electronic Engineering
  • Aerospace Engineering

Several topics frequently appear in their work, including:

  • Domain Adaptation and Few-Shot Learning
  • Advanced Neural Network Applications
  • Multimodal Machine Learning Applications
  • Video Surveillance and Tracking Methods
  • Human Pose and Action Recognition
  • Adversarial Robustness in Machine Learning
  • Explainable Artificial Intelligence (XAI)

Bernt Schiele has published significant papers in the following venues:

  • arXiv (Cornell University)
  • 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • Lecture Notes in Computer Science
  • International Journal of Computer Vision

Frequent co-authors collaborating with Schiele include:

  • Mario Fritz
  • Moritz Böhle
  • Dengxin Dai
  • Yongqin Xian
  • Shanshan Zhang

Notable publications authored or co-authored by Bernt Schiele are:

  • The Cityscapes Dataset for Semantic Urban Scene Understanding, 2024, arXiv (Cornell University)
  • SHIFT: A Synthetic Driving Dataset for Continuous Multi-Task Domain Adaptation, 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • SoftMatch: Addressing the Quantity-Quality Trade-off in Semi-supervised Learning, 2023, arXiv (Cornell University)
  • MTR++: Multi-Agent Motion Prediction With Symmetric Scene Modeling and Guided Intention Querying, 2024, IEEE Transactions on Pattern Analysis and Machine Intelligence
  • Hierarchical Online Instance Matching for Person Search, 2020, Proceedings of the AAAI Conference on Artificial Intelligence

Bernt Schiele has received the following awards:

  • German National Academy of Sciences Leopoldina (2021) in Informatics
  • Fellow of the International Association for Pattern Recognition (IAPR) (2018) for contributions to large-scale object recognition, human detection and pose estimation
  • IEEE Fellow (2017) for contributions to large-scale object recognition, human detection and pose estimation

Best Publications

  • The Cityscapes Dataset for Semantic Urban Scene Understanding

    Marius Cordts;Mohamed Omran;Sebastian Ramos;Timo Rehfeld

  • Pedestrian Detection: An Evaluation of the State of the Art

    P. Dollar;C. Wojek;B. Schiele;P. Perona

  • 2D Human Pose Estimation: New Benchmark and State of the Art Analysis

    Mykhaylo Andriluka;Leonid Pishchulin;Peter Gehler;Bernt Schiele

  • Generative adversarial text to image synthesis

    Scott Reed;Zeynep Akata;Xinchen Yan;Lajanugen Logeswaran

  • A tutorial on human activity recognition using body-worn inertial sensors

    Andreas Bulling;Ulf Blanke;Bernt Schiele

  • Pedestrian detection: A benchmark

    Piotr Dollar;Christian Wojek;Bernt Schiele;Pietro Perona

  • Zero-Shot Learning—A Comprehensive Evaluation of the Good, the Bad and the Ugly

    Yongqin Xian;Christoph H. Lampert;Bernt Schiele;Zeynep Akata

  • Robust Object Detection with Interleaved Categorization and Segmentation

    Bastian Leibe;Aleš Leonardis;Bernt Schiele

  • DeeperCut: A Deeper, Stronger, and Faster Multi-person Pose Estimation Model

    Eldar Insafutdinov;Leonid Pishchulin;Bjoern Andres;Mykhaylo Andriluka;Mykhaylo Andriluka

  • Meta-Transfer Learning for Few-Shot Learning

    Qianru Sun;Yaoyao Liu;Tat-Seng Chua;Bernt Schiele

  • People-tracking-by-detection and people-detection-by-tracking

    M. Andriluka;S. Roth;B. Schiele

  • Pedestrian detection in crowded scenes

    B. Leibe;E. Seemann;B. Schiele

  • Combined Object Categorization and Segmentation With an Implicit Shape Model

    Bastian Leibe;Ales Leonardis;Bernt Schiele

  • DeepCut: Joint Subset Partition and Labeling for Multi Person Pose Estimation

    Leonid Pishchulin;Eldar Insafutdinov;Siyu Tang;Bjoern Andres

  • Evaluation of output embeddings for fine-grained image classification

    Zeynep Akata;Scott Reed;Daniel Walter;Honglak Lee

  • Pictorial structures revisited: People detection and articulated pose estimation

    Mykhaylo Andriluka;Stefan Roth;Bernt Schiele

  • Feature Generating Networks for Zero-Shot Learning

    Yongqin Xian;Tobias Lorenz;Bernt Schiele;Zeynep Akata

  • Analyzing appearance and contour based methods for object categorization

    B. Leibe;B. Schiele

  • What Makes for Effective Detection Proposals

    Jan Hosang;Rodrigo Benenson;Piotr Dollar;Bernt Schiele

  • CityPersons: A Diverse Dataset for Pedestrian Detection

    Shanshan Zhang;Rodrigo Benenson;Bernt Schiele

  • Zero-Shot Learning with Structured Embeddings

    Zeynep Akata;Honglak Lee;Bernt Schiele

Frequent Co-Authors

Mario Fritz
Mario Fritz Helmholtz Center for Information Security
Rodrigo Benenson
Rodrigo Benenson Google (United States)
Mykhaylo Andriluka
Mykhaylo Andriluka Google (United States)
Marcus Rohrbach
Marcus Rohrbach Facebook (United States)
Zeynep Akata
Zeynep Akata University of Tübingen
Matthias Hein
Matthias Hein University of Tübingen
Bastian Leibe
Bastian Leibe RWTH Aachen University
Stefan Roth
Stefan Roth Technical University of Darmstadt
Siyu Tang
Siyu Tang ETH Zurich
James L. Crowley
James L. Crowley Grenoble Alpes University

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