Peter V. Gehler

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Amazon ∙ Max Planck Society

Learning Task-Specific Generalized Convolutions in the Permutohedral Lattice

Dense prediction tasks typically employ encoder-decoder architectures, b...
09/09/2019 ∙ by Anne S. Wannenwetsch, et al. ∙ 0 ∙ share

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

Direct prediction of 3D body pose and shape remains a challenge even for...
08/17/2018 ∙ by Mohamed Omran, et al. ∙ 14 ∙ share

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Semantic Video CNNs through Representation Warping

In this work, we propose a technique to convert CNN models for semantic ...
08/10/2017 ∙ by Raghudeep Gadde, et al. ∙ 0 ∙ share

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Towards Accurate Markerless Human Shape and Pose Estimation over Time

Existing marker-less motion capture methods often assume known backgroun...
07/24/2017 ∙ by Yinghao Huang, et al. ∙ 0 ∙ share

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A Generative Model of People in Clothing

We present the first image-based generative model of people in clothing ...
05/11/2017 ∙ by Christoph Lassner, et al. ∙ 0 ∙ share

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

3D models provide a common ground for different representations of human...
01/10/2017 ∙ by Christoph Lassner, et al. ∙ 0 ∙ share

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Video Propagation Networks

We propose a technique that propagates information forward through video...
12/16/2016 ∙ by Varun Jampani, et al. ∙ 0 ∙ share

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Reflectance Adaptive Filtering Improves Intrinsic Image Estimation

Separating an image into reflectance and shading layers poses a challeng...
12/15/2016 ∙ by Thomas Nestmeyer, et al. ∙ 0 ∙ share

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Efficient 2D and 3D Facade Segmentation using Auto-Context

This paper introduces a fast and efficient segmentation technique for 2D...
06/21/2016 ∙ by Raghudeep Gadde, et al. ∙ 0 ∙ share

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

Bilateral filters have wide spread use due to their edge-preserving prop...
03/17/2015 ∙ by Varun Jampani, et al. ∙ 0 ∙ share

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Permutohedral Lattice CNNs

This paper presents a convolutional layer that is able to process sparse...
12/20/2014 ∙ by Martin Kiefel, et al. ∙ 0 ∙ share

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The Informed Sampler: A Discriminative Approach to Bayesian Inference in Generative Computer Vision Models

Computer vision is hard because of a large variability in lighting, shap...
02/04/2014 ∙ by Varun Jampani, et al. ∙ 0 ∙ share

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Peter V. Gehler

Featured Co-authors

Bernt Schiele

Michael J. Black

Stefan Roth

Gerard Pons-Moll

Varun Jampani

Sebastian Nowozin

Angjoo Kanazawa

Javier Romero

Renaud Marlet

Christoph Lassner

Federica Bogo

Learning Task-Specific Generalized Convolutions in the Permutohedral Lattice

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

Semantic Video CNNs through Representation Warping

Towards Accurate Markerless Human Shape and Pose Estimation over Time

A Generative Model of People in Clothing

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

Video Propagation Networks

Reflectance Adaptive Filtering Improves Intrinsic Image Estimation

Efficient 2D and 3D Facade Segmentation using Auto-Context

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

Permutohedral Lattice CNNs

The Informed Sampler: A Discriminative Approach to Bayesian Inference in Generative Computer Vision Models