20 citations · 23 across the 4 of their papers we have counts for
4 papers
Chained Representation Cycling: Learning to Estimate 3D Human Pose and Shape by Cycling Between Representations
Nadine Rueegg, Christoph Lassner, Michael J. Black +1
The goal of many computer vision systems is to transform image pixels into 3D representations. Recent popular models use neural networks to regress directly from pixels to 3D objec…
Attacking Optical Flow
Anurag Ranjan, Joel Janai, Andreas Geiger +1
Deep neural nets achieve state-of-the-art performance on the problem of optical flow estimation. Since optical flow is used in several safety-critical applications like self-drivin…
Optical Flow Estimation using a Spatial Pyramid Network
Anurag Ranjan, Michael J. Black
We learn to compute optical flow by combining a classical spatial-pyramid formulation with deep learning. This estimates large motions in a coarse-to-fine approach by warping one i…
Keep it SMPL: Automatic Estimation of 3D Human Pose and Shape from a Single Image
Federica Bogo, Angjoo Kanazawa, Christoph Lassner +3
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. We estimate a full 3D mesh and show…