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2D Human Pose Estimation: New Benchmark and State of the Art Analysis
TLDR
We introduce a novel benchmark "MPII Human Pose" that makes a significant advance in terms of diversity and difficulty, a contribution that we feel is required for future developments in human body models. Expand
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Keep It SMPL: Automatic Estimation of 3D Human Pose and Shape from a Single Image
TLDR
We describe the first method to automatically estimate the 3D pose of the human body as well as its 3D shape from a single unconstrained image. Expand
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On feature combination for multiclass object classification
TLDR
A key ingredient in the design of visual object classification systems is the identification of relevant class specific aspects while being robust to intra-class variations. Expand
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Bayesian color constancy revisited
TLDR
In this paper we follow a line of research that assumes uniform illumination of a scene, and that the principal step in estimating reflectances is the estimation of the scene illuminant. Expand
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DeepCut: Joint Subset Partition and Labeling for Multi Person Pose Estimation
TLDR
We propose an approach that jointly solves the tasks of detection and pose estimation of multiple people in a scene, identifies occluded body parts, and disambiguates body parts between people in close proximity of each other. Expand
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Unite the People: Closing the Loop Between 3D and 2D Human Representations
TLDR
We propose a hybrid approach to this problem: with an extended version of the recently introduced SMPLify method, we obtain high quality 3D body model fits for multiple human pose datasets. Expand
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Teaching 3D geometry to deformable part models
TLDR
We extend the successful discriminatively trained deformable part models to include both estimates of viewpoint and 3D parts that are consistent across viewpoints. Expand
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Recovering Intrinsic Images with a Global Sparsity Prior on Reflectance
TLDR
We address the challenging task of decoupling material properties from lighting properties given a single image. Expand
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Video Propagation Networks
TLDR
We propose a generic neural network architecture that propagates information across video frames in an adaptive manner. Expand
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Neural Body Fitting: Unifying Deep Learning and Model Based Human Pose and Shape Estimation
TLDR
In this paper, we propose a novel approach (Neural Body Fitting (NBF)) that integrates a statistical body model as a layer within a CNN leveraging both reliable bottom-up body part segmentation and robust top-down body model constraints. Expand
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