14 citations · 19 across the 5 of their papers we have counts for
6 papers · 1 filter
Generative Zoo
Tomasz Niewiadomski, Anastasios Yiannakidis, Hanz Cuevas-Velasquez +4
The model-based estimation of 3D animal pose and shape from images enables computational modeling of animal behavior. Training models for this purpose requires large amounts of lab…
Reconstructing Animals and the Wild
Peter Kulits, Michael J. Black, Silvia Zuffi
The idea of 3D reconstruction as scene understanding is foundational in computer vision. Reconstructing 3D scenes from 2D visual observations requires strong priors to disambiguate…
AWOL: Analysis WithOut synthesis using Language
Silvia Zuffi, Michael J. Black
Many classical parametric 3D shape models exist, but creating novel shapes with such models requires expert knowledge of their parameters. For example, imagine creating a specific…
OSSO: Obtaining Skeletal Shape from Outside
Marilyn Keller, Silvia Zuffi, Michael J. Black +1
We address the problem of inferring the anatomic skeleton of a person, in an arbitrary pose, from the 3D surface of the body; i.e. we predict the inside (bones) from the outside (s…
hSMAL: Detailed Horse Shape and Pose Reconstruction for Motion Pattern Recognition
Ci Li, Nima Ghorbani, Sofia Broomé +5
In this paper we present our preliminary work on model-based behavioral analysis of horse motion. Our approach is based on the SMAL model, a 3D articulated statistical model of ani…
Three-D Safari: Learning to Estimate Zebra Pose, Shape, and Texture from Images "In the Wild"
Silvia Zuffi, Angjoo Kanazawa, Tanya Berger-Wolf +1
We present the first method to perform automatic 3D pose, shape and texture capture of animals from images acquired in-the-wild. In particular, we focus on the problem of capturing…