• Publications
  • Influence
2D Human Pose Estimation: New Benchmark and State of the Art Analysis
TLDR
A novel benchmark "MPII Human Pose" is introduced that makes a significant advance in terms of diversity and difficulty, a contribution that is required for future developments in human body models. Expand
Keep It SMPL: Automatic Estimation of 3D Human Pose and Shape from a Single Image
TLDR
The first method to automatically estimate the 3D pose of the human body as well as its 3D shape from a single unconstrained image is described, showing superior pose accuracy with respect to the state of the art. Expand
On feature combination for multiclass object classification
  • P. Gehler, S. Nowozin
  • Computer Science
  • IEEE 12th International Conference on Computer…
  • 1 September 2009
TLDR
Several models that aim at learning the correct weighting of different features from training data are studied, including multiple kernel learning as well as simple baseline methods and ensemble methods inspired by Boosting are derived. Expand
Bayesian color constancy revisited
TLDR
This paper introduces a new tool in the form of a database of 568 high-quality, indoor and outdoor images, accurately labelled with illuminant, and preserved in their raw form, free of correction or normalisation, which shows that automatic selection of grey-world algorithms according to image properties is not nearly so effective as has been thought. Expand
DeepCut: Joint Subset Partition and Labeling for Multi Person Pose Estimation
TLDR
An approach that jointly solves the tasks of detection and pose estimation: it infers the number of persons in a scene, identifies occluded body parts, and disambiguates body parts between people in close proximity of each other is proposed. Expand
Unite the People: Closing the Loop Between 3D and 2D Human Representations
TLDR
This work proposes a hybrid approach to 3D body model fits for multiple human pose datasets with an extended version of the recently introduced SMPLify method, and shows that UP-3D can be enhanced with these improved fits to grow in quantity and quality, which makes the system deployable on large scale. Expand
Neural Body Fitting: Unifying Deep Learning and Model Based Human Pose and Shape Estimation
TLDR
A novel approach (Neural Body Fitting (NBF) is proposed 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
Video Propagation Networks
TLDR
A Video Propagation Network that processes video frames in an adaptive manner that combines two components, a temporal bilateral network for dense and video adaptive filtering, followed by a spatial network to refine features and increased flexibility. Expand
Teaching 3D geometry to deformable part models
TLDR
This paper extends the successful discriminatively trained deformable part models to include both estimates of viewpoint and 3D parts that are consistent across viewpoints, and experimentally verify that adding 3D geometric information comes at minimal performance loss w.r.t. Expand
Recovering Intrinsic Images with a Global Sparsity Prior on Reflectance
TLDR
This work introduces a new prior on reflectance, that results in a Random Field model with global, latent variables (basis colors) and pixel-accurate output reflectance values, and shows that without edge information high-quality results can be achieved, that are on par with methods exploiting this source of information. Expand
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