A Generative Model of People in ClothingChristoph Lassner , Gerard Pons-Moll , and Peter Gehler International Conference on Computer Vision (ICCV) |
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A Generative Model of People in ClothingChristoph Lassner , Gerard Pons-Moll , and Peter Gehler International Conference on Computer Vision (ICCV) |
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Semantic Video CNNs through Representation WarpingRaghudeep Gadde , Varun Jampani , and Peter Gehler International Conference on Computer Vision (ICCV) |
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Learning To Filter Object DetectionsSergey Prokudin , Daniel Kappler , Sebastian Nowozin , and Peter Gehler German Conference on Patter Recognition (GCPR) |
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A Curious Problem with Using the Colour Checker Dataset for Illuminant EstimationGhalia Hemrit , Graham Finlayson , Peter Gehler , and Arjan Gijsenij Color and Imaging Conference (CIC) |
Reflectance Adaptive Filtering Improves Intrinsic Image EstimationThomas Nestmeyer and Peter Gehler Computer Vision and Pattern Recognition (CVPR) |
Video Propagation NetworksVarun Jampani , Raghudeep Gadde , and Peter Gehler Computer Vision and Pattern Recognition (CVPR) |
Unite the People: Closing the Loop Between 3D and 2D Human RepresentationsChristoph Lassner , Javier Romero , Martin Kiefel , Federica Bogo , Michael Black , and Peter Gehler Computer Vision and Pattern Recognition (CVPR) |
Efficient 2D and 3D Facade Segmentation using Auto-ContextRaghudeep Gadde , Varun Jampani , Renaud Marlet , and Peter Gehler Pattern Analysis and Machine Intelligence (PAMI) |
barrista -- caffe well servedChristoph Lassner , Martin Kiefel , Daniel Kappler , and Peter Gehler Multimedia 2016 Open Source Software Competition (ACMMM) |
Superpixel Convolutional Networks using Bilateral InceptionsRaghudeep Gadde , Varun Jampani , Martin Kiefel , Daniel Kappler , and Peter Gehler Proceedings of the European Conference on Computer Vision (ECCV) |
Keep it SMPL: Automatic Estimation of 3D Human Pose and Shape from a Single ImageFederica Bogo , Angjoo Kanazawa , Christoph Lassner , Peter Gehler , Javier Romero , and Michael Black Proceedings of the European Conference on Computer Vision (ECCV) |
DeepCut: Joint Subset Partition and Labeling for Multi Person Pose EstimationLeonid Pishchulin , Eldar Insafutdinov , Siyu Tang , Björn Andres , Mykhaylo Andriluka , Peter Gehler , and Bernt Schiele Computer Vision and Pattern Recognition (CVPR) |
Learning Sparse High Dimensional Filters: Image Filtering, Dense CRFs and Bilateral Neural NetworksVarun Jampani , Martin Kiefel , and Peter Gehler Computer Vision and Pattern Recognition (CVPR) |
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Proceedings of the 37th German Conference on Pattern RecognitionJürgen Gall , Peter Gehler , and Bastian Leibe GCPR Proceedings |
3D Object Class Detection in the WildBojan Pepik , Michael Stark , Peter Gehler , Tobias Ritschel , and Bernt Schiele CVPR workshop on 3D from a Single Image (CVPR-W) |
Permutohedral Lattice CNNsMartin Kiefel , Varun Jampani , and Peter Gehler International Confenrence on Learning Representation Workshops |
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The Informed Sampler: A Discriminative Approach to Bayesian Inference in Generative Computer Vision ModelsVarun Jampani , Sebastian Nowozin , Matt Loper , and Peter Gehler Computer Vision and Image Understanding (CVIU) |
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Multi-view and 3D Deformable Part ModelsBojan Pepik , Michael Stark , Peter Gehler , and Bernt Schiele Pattern Analysis and Machine Intelligence (PAMI) |
Efficient Facade Segmentation using Auto-ContextVarun Jampani , Raghudeep Gadde , and Peter Gehler Winter Conference on Applications of Computer Vision (WACV) |
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Advanced Structured PredictionSebastian Nowozin , Peter Gehler , Jeremy Jancsary , and Christoph Lampert MIT press |
Intrinsic VideoNaejin Kong , Peter Gehler , and Michael Black Proceedings of the European Conference on Computer Vision (ECCV) |
Human Pose Estimation with Fields of PartsMartin Kiefel and Peter Gehler Proceedings of the European Conference on Computer Vision (ECCV) |
Efficient Non-linear Markov Models for Human MotionAndreas Lehrmann , Peter Gehler , and Sebastian Nowozin Computer Vision and Pattern Recognition (CVPR) |
Human Pose Estimation: New Benchmark and State of the Art AnalysisMykhaylo Andriluka , Leonid Pishchulin , Peter Gehler , and Bernt Schiele Computer Vision and Pattern Recognition (CVPR) |
Multi-View Priors for Learning Detectors from Sparse Viewpoint DataBojan Pepik , Michael Stark , Peter Gehler , and Bernt Schiele International Conference on Learning Representations (ICLR) |
Strong Appearance and Expressive Spatial Models for Human Pose EstimationLeonid Pishchulin , Mykhaylo Andriluka , Peter Gehler , and Bernt Schiele International Conference on Computer Vision (ICCV) |
A Non-parametric Bayesian Network Prior of Human PoseAndreas Lehrmann , Peter Gehler , and Sebastian Nowozin International Conference on Computer Vision (ICCV) |
Branch&Rank for Efficient Object DetectionAlain Lehmann , Peter Gehler , and Luc Van Gool International Journal of Computer Vision (IJCV) |
Poselet conditioned pictorial structuresLeonid Pishchulin , Mykhaylo Andriluka , Peter Gehler , and Bernt Schiele IEEE Conference on Computer Vision and Pattern Recognition (CVPR) |
Occlusion Patterns for Object Class DetectionBojan Pepik , Michael Stark , Peter Gehler , and Bernt Schiele IEEE Conference on Computer Vision and Pattern Recognition (CVPR) |
3D2PM - 3D Deformable Part ModelsBojan Pepik , Peter Gehler , Michael Stark , and Bernt Schiele Proceedings of the European Conference on Computer Vision (ECCV) |
Pottics - The Potts Topic Model for Semantic Image SegmentationChristoph Dann , Peter Gehler , Stefan Roth , and Sebastian Nowozin Proceedings of 34th DAGM Symposium (DAGM) |
Teaching 3D Geometry to Deformable Part ModelsBojan Pepik , Michael Stark , Peter Gehler , and Bernt Schiele IEEE Conference on Computer Vision and Pattern Recognition (CVPR) |
Learning Search Based Inference for Object DetectionPeter Gehler and Alain Lehmann ICML workshop on Inferning |
Recovering Intrinsic Images with a Global Sparsity Prior on ReflectancePeter Gehler , Carsten Rother , Martin Kiefel , Lumin Zhang , and Bernhard Schölkopf Advances in Neural Information Processing Systems (NIPS) |
Branch&Rank - Non-Linear Object DetectionAlain Lehmann , Peter Gehler , and Luc Van Gool Proceedings of the British Machine Vision Conference (BMVC) |
Learning Output Kernels with Block Coordinate DescentFrancesco Dinuzzo , Cheng Soon Ong , Peter Gehler , and Gianluigi Pillonetto International Conference on Machine Learning (ICML) |
Scene Carving - Scene Consistent Image RetargetingAlex Mansfield , Peter Gehler , Luc Van Gool , and Carsten Rother European Conference on Computer Vision (ECCV) |
Visibility Maps for Improving Seam CarvingAlex Mansfield , Peter Gehler , Luc Van Gool , and Carsten Rother Media Retargeting Workshop (ECCV) pdf bib supplementary poster slides project page code scholar |
On Parameter Learning in CRF-based Approaches to Object Class Image SegmentationSebastian Nowozin , Peter Gehler , and Christoph Lampert European Conference on Computer Vision (ECCV) |
An introduction to Kernel Learning AlgorithmsPeter Gehler and Bernhard Schölkopf In Kernel Methods for Remote Sensing Data Analysis |
Let the kernel figure it out; Principled learning of pre-processing for kernel classifiersPeter Gehler and Sebastian Nowozin Proceedings of the Conference on Computer Vision and Pattern Recognition (CVPR) |
On feature combination for multiclass object classificationPeter Gehler and Sebastian Nowozin International Conference on Computer Vision (ICCV) |
Infinite Kernel LearningPeter Gehler and Sebastian Nowozin Kernel Learning - Automatic Selection of Optimal Kernels (NIPS workshop on Kernel Learning) |
Infinite Kernel LearningPeter Gehler and Sebastian Nowozin Technical Report 178, Max Planck Institute |
Bayesian Color Constancy RevisitedPeter Gehler , Carsten Rother , Andrew Blake , Tom Minka , and Toby Sharp IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR) |
Deterministic Annealing for Multiple-Instance LearningPeter Gehler and Olivier Chapelle Artificial Intelligence and Statistics (AIStats) |
Implicit Wiener Series, Part II Regularised estimationPeter Gehler and Matthias O. Franz Technical Report 148, Max Planck Institute |
The rate adapting poisson model for information retrieval and object recognitionPeter Gehler , Alex Holub , and Max Welling Proceedings of the 23rd international conference on Machine learning (ICML) |
Products of ``Edge-perts''Peter Gehler and Max Welling Advances in Neural Information Processing Systems 18 (NIPS) |
How to choose the covariance for Gaussian process regression independently of the basisMatthias O. Franz and Peter Gehler Proceedings of the Workshop Gaussian Processes in Practice |