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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…
3D Menagerie: Modeling the 3D shape and pose of animals
Silvia Zuffi, Angjoo Kanazawa, David Jacobs +1
There has been significant work on learning realistic, articulated, 3D models of the human body. In contrast, there are few such models of animals, despite many applications. The m…
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…
Optical Flow with Semantic Segmentation and Localized Layers
Laura Sevilla-Lara, Deqing Sun, Varun Jampani +1
Existing optical flow methods make generic, spatially homogeneous, assumptions about the spatial structure of the flow. In reality, optical flow varies across an image depending on…