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Peter V. Gehler

Peter V. Gehler

D-Index & Metrics

Computer Science

D-Index
47
Citations
15564
World Ranking
6315
National Ranking
292

Overview

Peter V. Gehler is affiliated with Zalando SE in Germany and primarily publishes in the field of computer science, with a focus on artificial intelligence and computer vision. Their research spans several subfields including domain adaptation, anomaly detection, multimodal machine learning, and generative adversarial networks. The scientist's body of work reflects a strong engagement with machine learning techniques and applications, as well as cancer research and radiological imaging.

Recent papers authored or coauthored by Peter V. Gehler include:

  • "Towards Total Recall in Industrial Anomaly Detection," 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • "CrossCLR: Cross-modal Contrastive Learning For Multi-modal Video Representations," 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • "Assaying Out-Of-Distribution Generalization in Transfer Learning," 2022, arXiv (Cornell University)
  • "TeST: Test-time Self-Training under Distribution Shift," 2023, 2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)
  • "Towards causal generative scene models via competition of experts," 2020, arXiv (Cornell University)

The researcher collaborates frequently with several notable coauthors including:

  • Bernhard Schölkopf
  • Francesco Locatello
  • Julius von Kügelgen
  • Matthias Bethge
  • Thomas Brox

Peter V. Gehler's work has been published predominantly in these venues:

  • arXiv (Cornell University)
  • Zenodo (CERN European Organization for Nuclear Research)
  • 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • 2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)

The main topics covered in their publications include:

  • Domain Adaptation and Few-Shot Learning
  • Anomaly Detection Techniques and Applications
  • Multimodal Machine Learning Applications
  • Generative Adversarial Networks and Image Synthesis
  • Cancer-related molecular mechanisms research
  • Machine Learning and Data Classification
  • Adversarial Robustness in Machine Learning

Best Publications

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

    Mykhaylo Andriluka;Leonid Pishchulin;Peter Gehler;Bernt Schiele

  • Keep It SMPL: Automatic Estimation of 3D Human Pose and Shape from a Single Image

    Federica Bogo;Angjoo Kanazawa;Christoph Lassner;Christoph Lassner;Peter V. Gehler;Peter V. Gehler

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

    Leonid Pishchulin;Eldar Insafutdinov;Siyu Tang;Bjoern Andres

  • Towards Total Recall in Industrial Anomaly Detection

    Karsten Roth;Latha Pemula;Joaquin Zepeda;Bernhard Schölkopf

  • On feature combination for multiclass object classification

    Peter Gehler;Sebastian Nowozin

  • Unite the People: Closing the Loop Between 3D and 2D Human Representations

    Christoph Lassner;Javier Romero;Martin Kiefel;Federica Bogo

  • Bayesian color constancy revisited

    P.V. Gehler;C. Rother;A. Blake;T. Minka

  • Neural Body Fitting: Unifying Deep Learning and Model Based Human Pose and Shape Estimation

    Mohamed Omran;Christoph Lassner;Gerard Pons-Moll;Peter Gehler

  • Kernel methods for remote sensing data analysis

    Gustavo Camps-Valls;Lorenzo Bruzzone

  • Poselet Conditioned Pictorial Structures

    Leonid Pishchulin;Mykhaylo Andriluka;Peter Gehler;Bernt Schiele

  • Teaching 3D geometry to deformable part models

    Bojan Pepik;Michael Stark;Peter Gehler;Bernt Schiele

  • Strong Appearance and Expressive Spatial Models for Human Pose Estimation

    Leonid Pishchulin;Mykhaylo Andriluka;Peter Gehler;Bernt Schiele

  • Video Propagation Networks

    Varun Jampani;Raghudeep Gadde;Peter V. Gehler

  • A Generative Model of People in Clothing

    Christoph Lassner;Gerard Pons-Moll;Peter V. Gehler

  • Learning Sparse High Dimensional Filters: Image Filtering, Dense CRFs and Bilateral Neural Networks

    Varun Jampani;Martin Kiefel;Peter V. Gehler

  • Semantic Video CNNs Through Representation Warping

    Raghudeep Gadde;Varun Jampani;Peter V. Gehler

  • Efficient Nonlinear Markov Models for Human Motion

    Andreas M. Lehrmann;Peter V. Gehler;Sebastian Nowozin

  • Occlusion Patterns for Object Class Detection

    Bojan Pepikj;Michael Stark;Peter Gehler;Bernt Schiele

  • The rate adapting poisson model for information retrieval and object recognition

    Peter V. Gehler;Alex D. Holub;Max Welling

  • Recovering Intrinsic Images with a Global Sparsity Prior on Reflectance

    Carsten Rother;Martin Kiefel;Lumin Zhang;Bernhard Schölkopf

Frequent Co-Authors

Sebastian Nowozin
Sebastian Nowozin Microsoft (United States)
Christoph H. Lampert
Christoph H. Lampert Institute of Science and Technology Austria
Bernt Schiele
Bernt Schiele Max Planck Institute for Informatics
Mykhaylo Andriluka
Mykhaylo Andriluka Google (United States)
Carsten Rother
Carsten Rother Heidelberg University
Michael J. Black
Michael J. Black Max Planck Institute for Intelligent Systems
Bernhard Schölkopf
Bernhard Schölkopf Max Planck Institute for Intelligent Systems
Gerard Pons-Moll
Gerard Pons-Moll University of Tübingen
Graham D. Finlayson
Graham D. Finlayson University of East Anglia

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