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Learning Task-Specific Generalized Convolutions in the Permutohedral Lattice
Dense prediction tasks typically employ encoder-decoder architectures, b...
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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...
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Semantic Video CNNs through Representation Warping
In this work, we propose a technique to convert CNN models for semantic ...
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Towards Accurate Markerless Human Shape and Pose Estimation over Time
Existing marker-less motion capture methods often assume known backgroun...
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A Generative Model of People in Clothing
We present the first image-based generative model of people in clothing ...
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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...
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Video Propagation Networks
We propose a technique that propagates information forward through video...
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Reflectance Adaptive Filtering Improves Intrinsic Image Estimation
Separating an image into reflectance and shading layers poses a challeng...
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Efficient 2D and 3D Facade Segmentation using Auto-Context
This paper introduces a fast and efficient segmentation technique for 2D...
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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...
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Permutohedral Lattice CNNs
This paper presents a convolutional layer that is able to process sparse...
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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...
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