On the fair use of the ColorChecker dataset for illuminant estimation
Massimo Buzzelli, Graham Finlayson, Arjan Gijsenij, Peter Gehler, Mark Drew, Lilong Shi, and Luca Cogo
Journal of Physics: Conference Series, 2025
Exploring Fit and Shape for Predicting Garment Size Issues in Fashion with Multi-task Learning
Sahar Mbarek, Leonidas Lefakis, Peter Gehler, Sonia Aurelio, Rodrigo Weffer, and Reza Shirvany
Revolutionizing Fashion and Retail, 2025
Alias-Free GAN for 3D-Aware Image Generation
Attila Szabó, Yevgeniy Puzikov, Sahan Ayvaz, Sonia Aurelio, Peter Gehler, Reza Shirvany, and Malte Alf
International Conference on Computer Vision Theory and Applications (VISAPP), 2024
Towards Total Recall in Industrial Anomaly Detection
Karsten Roth, Latha Pemula, Joaquin Zepeda, Bernhard Schölkopf, Thomas Brox, and Peter Gehler
Computer Vision and Pattern Recognition (CVPR), 2022
You Mostly Walk Alone: Analyzing Feature Attribution in Trajectory Prediction
Osama Makansi, Julius von Kuegelen, Francesco Locatello, Peter Gehler, Dominik Janzing, Thomas Brox, and Bernhard Schölkopf
International Conference on Learning Representations (ICLR), 2022
The Role of Pretrained Representations for the OOD Generalization of RL Agents
Andrea Dittadi, Frederik Traeuble, Manuel Wüthrich, Felix Widmaier, Peter Gehler, Ole Winther, Francesco Locatello, Olivier Bachem, Bernhard Schölkopf, and Stefan Bauer
International Conference on Learning Representations (ICLR), 2022
Visual Representation Learning Does Not Generalize Strongly Within the Same Domain
Lukas Schott, Julius von Kuegelen, Frederik Traeuble, Peter Gehler, Chris Russell, Matthias Bethge, Bernhard Schölkopf, Francesco Locatello, and Wieland Brendl
International Conference on Learning Representations (ICLR), 2022
Dynamic Inference with Neural Interpreters
Muhammad Waleed Gondal, Nasim Rahaman, Shruti Joshi, Peter Gehler, Yoshua Bengio, Francesco Locatello, and Bernhard Schölkopf
Neural Information Processing Systems (NeurIPS), 2021
Backward-Compatible Prediction Updates: A Probabilistic Approach
Frederik Traeuble, Julius von Kuegelen, Matthäus Kleindessner, Francesco Locatello, Bernhard Schölkopf, and Peter Gehler
Neural Information Processing Systems (NeurIPS), 2021
CrossCLR: Cross-modal Contrastive Learning For Multi-modal Video Representations
Mohammadreza Zolfaghari, Yi Zhu, Peter Gehler, and Thomas Brox
International Conference on Computer Vision (ICCV), 2021
Adapting ImageNet-scale models to complex distribution shifts with self-learning
Evgenia Rusak, Steffen Schneider, Peter Gehler, Oliver Bringmann, Wieland Brendl, and Matthias Bethge
ICLR workshop on Weakly Supervised Learning (ICLR-w), 2021
Towards causal generative scene models via competition of experts
Julius von Kuegelen, Ivan Ustyuzhaninov, Peter Gehler, Matthias Bethge, and Bernhard Schölkopf
ICLR workshop on Causal Learning for Decision Making (ICLR-w), 2020
Learning Task-Specific Generalized Convolutions in the Permutohedral Lattice
Anne Wannenwetsch, Martin Kiefel, Peter Gehler, and Stefan Roth
German Conference on Pattern Recognition (GCPR), 2019
Learning an event sequence embedding for dense event-based deep stereo
Stepan Tulyakov, Francois Fleuret, Martin Kiefel, Peter Gehler, and Michael Hirsch
International Conference on Computer Vision (ICCV), 2019
Providing a single Ground-truth for Illuminant Estimation for the ColorChecker Dataset
Ghalia Hemrit, Graham Finlayson, Arjan Gijsenij, Peter Gehler, Simone Bianco, Mark Drew, Brian Funt, and Lilong Shi
Pattern Analysis and Machine Intelligence (PAMI), 2019
Deep Directional Statistics: Pose Estimation with Uncertainty Quantification
Sergey Prokudin, Peter Gehler, and Sebastian Nowozin
European Conference on Computer Vision (ECCV), 2018
Neural Body Fitting: Unifying Deep Learning and Model Based Human Pose and Shape Estimation
Mohamed Omran, Christoph Lassner, Gerard Pons-Moll, Peter Gehler, and Bernt Schiele
International Conference on 3DVision (3DV), 2018
A Generative Model of People in Clothing
Christoph Lassner, Gerard Pons-Moll, and Peter Gehler
International Conference on Computer Vision (ICCV), 2017
Semantic Video CNNs through Representation Warping
Raghudeep Gadde, Varun Jampani, and Peter Gehler
International Conference on Computer Vision (ICCV), 2017
Towards Accurate Marker-less Human Shape and Pose Estimation over Time
Yinghao Huang, Federica Bogo, Christoph Lassner, Angjoo Kanazawa, Peter Gehler, Javier Romero, Ijaz Akther, and Michael Black
International Conference on 3D Vision (3DV), 2017
Learning To Filter Object Detections
Sergey Prokudin, Daniel Kappler, Sebastian Nowozin, and Peter Gehler
German Conference on Pattern Recognition (GCPR), 2017
A Curious Problem with Using the Colour Checker Dataset for Illuminant Estimation
Ghalia Hemrit, Graham Finlayson, Peter Gehler, and Arjan Gijsenij
Color and Imaging Conference (CIC), 2017
Reflectance Adaptive Filtering Improves Intrinsic Image Estimation
Thomas Nestmeyer and Peter Gehler
Computer Vision and Pattern Recognition (CVPR), 2017
Video Propagation Networks
Varun Jampani, Raghudeep Gadde, and Peter Gehler
Computer Vision and Pattern Recognition (CVPR), 2017
Unite the People: Closing the Loop Between 3D and 2D Human Representations
Christoph Lassner, Javier Romero, Martin Kiefel, Federica Bogo, Michael Black, and Peter Gehler
Computer Vision and Pattern Recognition (CVPR), 2017
Efficient 2D and 3D Facade Segmentation using Auto-Context
Raghudeep Gadde, Varun Jampani, Renaud Marlet, and Peter Gehler
Pattern Analysis and Machine Intelligence (PAMI), 2017
barrista -- caffe well served
Christoph Lassner, Martin Kiefel, Daniel Kappler, and Peter Gehler
Multimedia 2016 Open Source Software Competition (ACMMM), 2016
Superpixel Convolutional Networks using Bilateral Inceptions
Raghudeep Gadde, Varun Jampani, Martin Kiefel, Daniel Kappler, and Peter Gehler
Proceedings of the European Conference on Computer Vision (ECCV), 2016
Keep it SMPL: Automatic Estimation of 3D Human Pose and Shape from a Single Image
Federica Bogo, Angjoo Kanazawa, Christoph Lassner, Peter Gehler, Javier Romero, and Michael Black
Proceedings of the European Conference on Computer Vision (ECCV), 2016
DeepCut: Joint Subset Partition and Labeling for Multi Person Pose Estimation
Leonid Pishchulin, Eldar Insafutdinov, Siyu Tang, Björn Andres, Mykhaylo Andriluka, Peter Gehler, and Bernt Schiele
Computer Vision and Pattern Recognition (CVPR), 2016
Learning Sparse High Dimensional Filters: Image Filtering, Dense CRFs and Bilateral Neural Networks
Varun Jampani, Martin Kiefel, and Peter Gehler
Computer Vision and Pattern Recognition (CVPR), 2016
Proceedings of the 37th German Conference on Pattern Recognition
Jürgen Gall, Peter Gehler, and Bastian Leibe
GCPR Proceedings, 2015
3D Object Class Detection in the Wild
Bojan Pepik, Michael Stark, Peter Gehler, Tobias Ritschel, and Bernt Schiele
CVPR workshop on 3D from a Single Image (CVPR-W), 2015
Permutohedral Lattice CNNs
Martin Kiefel, Varun Jampani, and Peter Gehler
International Conference on Learning Representations Workshops, 2015
The Informed Sampler: A Discriminative Approach to Bayesian Inference in Generative Computer Vision Models
Varun Jampani, Sebastian Nowozin, Matt Loper, and Peter Gehler
Computer Vision and Image Understanding (CVIU), 2015
Multi-view and 3D Deformable Part Models
Bojan Pepik, Michael Stark, Peter Gehler, and Bernt Schiele
Pattern Analysis and Machine Intelligence (PAMI), 2015
Efficient Facade Segmentation using Auto-Context
Varun Jampani, Raghudeep Gadde, and Peter Gehler
Winter Conference on Applications of Computer Vision (WACV), 2015
Advanced Structured Prediction
Sebastian Nowozin, Peter Gehler, Jeremy Jancsary, and Christoph Lampert
MIT Press, 2014
Intrinsic Video
Naejin Kong, Peter Gehler, and Michael Black
Proceedings of the European Conference on Computer Vision (ECCV), 2014
Human Pose Estimation with Fields of Parts
Martin Kiefel and Peter Gehler
Proceedings of the European Conference on Computer Vision (ECCV), 2014
Efficient Non-linear Markov Models for Human Motion
Andreas Lehrmann, Peter Gehler, and Sebastian Nowozin
Computer Vision and Pattern Recognition (CVPR), 2014
Human Pose Estimation: New Benchmark and State of the Art Analysis
Mykhaylo Andriluka, Leonid Pishchulin, Peter Gehler, and Bernt Schiele
Computer Vision and Pattern Recognition (CVPR), 2014
Multi-View Priors for Learning Detectors from Sparse Viewpoint Data
Bojan Pepik, Michael Stark, Peter Gehler, and Bernt Schiele
International Conference on Learning Representations (ICLR), 2014
Strong Appearance and Expressive Spatial Models for Human Pose Estimation
Leonid Pishchulin, Mykhaylo Andriluka, Peter Gehler, and Bernt Schiele
International Conference on Computer Vision (ICCV), 2013
A Non-parametric Bayesian Network Prior of Human Pose
Andreas Lehrmann, Peter Gehler, and Sebastian Nowozin
International Conference on Computer Vision (ICCV), 2013
Branch&Rank for Efficient Object Detection
Alain Lehmann, Peter Gehler, and Luc Van Gool
International Journal of Computer Vision (IJCV), 2013
Poselet conditioned pictorial structures
Leonid Pishchulin, Mykhaylo Andriluka, Peter Gehler, and Bernt Schiele
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2013
Occlusion Patterns for Object Class Detection
Bojan Pepik, Michael Stark, Peter Gehler, and Bernt Schiele
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2013
3D2PM - 3D Deformable Part Models
Bojan Pepik, Peter Gehler, Michael Stark, and Bernt Schiele
Proceedings of the European Conference on Computer Vision (ECCV), 2012
Pottics - The Potts Topic Model for Semantic Image Segmentation
Christoph Dann, Peter Gehler, Stefan Roth, and Sebastian Nowozin
Proceedings of 34th DAGM Symposium (DAGM), 2012
Teaching 3D Geometry to Deformable Part Models
Bojan Pepik, Michael Stark, Peter Gehler, and Bernt Schiele
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2012
Learning Search Based Inference for Object Detection
Peter Gehler and Alain Lehmann
ICML workshop on Inferning, 2012
Recovering Intrinsic Images with a Global Sparsity Prior on Reflectance
Peter Gehler, Carsten Rother, Martin Kiefel, Lumin Zhang, and Bernhard Schölkopf
Advances in Neural Information Processing Systems (NIPS), 2011
Branch&Rank - Non-Linear Object Detection
Alain Lehmann, Peter Gehler, and Luc Van Gool
Proceedings of the British Machine Vision Conference (BMVC), 2011
Learning Output Kernels with Block Coordinate Descent
Francesco Dinuzzo, Cheng Soon Ong, Peter Gehler, and Gianluigi Pillonetto
International Conference on Machine Learning (ICML), 2011
Scene Carving - Scene Consistent Image Retargeting
Alex Mansfield, Peter Gehler, Luc Van Gool, and Carsten Rother
European Conference on Computer Vision (ECCV), 2010
Visibility Maps for Improving Seam Carving
Alex Mansfield, Peter Gehler, Luc Van Gool, and Carsten Rother
Media Retargeting Workshop (ECCV), 2010
On Parameter Learning in CRF-based Approaches to Object Class Image Segmentation
Sebastian Nowozin, Peter Gehler, and Christoph Lampert
European Conference on Computer Vision (ECCV), 2010
An introduction to Kernel Learning Algorithms
Peter Gehler and Bernhard Schölkopf
In Kernel Methods for Remote Sensing Data Analysis, 2009
Let the kernel figure it out; Principled learning of pre-processing for kernel classifiers
Peter Gehler and Sebastian Nowozin
Proceedings of the Conference on Computer Vision and Pattern Recognition (CVPR), 2009
On feature combination for multiclass object classification
Peter Gehler and Sebastian Nowozin
International Conference on Computer Vision (ICCV), 2009
Infinite Kernel Learning
Peter Gehler and Sebastian Nowozin
Kernel Learning - Automatic Selection of Optimal Kernels (NIPS workshop on Kernel Learning), 2008
Infinite Kernel Learning
Peter Gehler and Sebastian Nowozin
Technical Report 178, Max Planck Institute, 2008
Bayesian Color Constancy Revisited
Peter Gehler, Carsten Rother, Andrew Blake, Tom Minka, and Toby Sharp
IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), 2008
Deterministic Annealing for Multiple-Instance Learning
Peter Gehler and Olivier Chapelle
Artificial Intelligence and Statistics (AIStats), 2007
Implicit Wiener Series, Part II Regularised estimation
Peter Gehler and Matthias O. Franz
Technical Report 148, Max Planck Institute, 2006
The rate adapting poisson model for information retrieval and object recognition
Peter Gehler, Alex Holub, and Max Welling
Proceedings of the 23rd international conference on Machine learning (ICML), 2006
Products of "Edge-perts"
Peter Gehler and Max Welling
Advances in Neural Information Processing Systems 18 (NIPS), 2006
How to choose the covariance for Gaussian process regression independently of the basis
Matthias O. Franz and Peter Gehler
Proceedings of the Workshop Gaussian Processes in Practice, 2006