Search Results for author: Silvia Zuffi

Found 9 papers, 2 papers with code

OSSO: Obtaining Skeletal Shape from Outside

1 code implementation CVPR 2022 Marilyn Keller, Silvia Zuffi, Michael J. Black, Sergi Pujades

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 (skin).

BARC: Learning to Regress 3D Dog Shape from Images by Exploiting Breed Information

no code implementations CVPR 2022 Nadine Rueegg, Silvia Zuffi, Konrad Schindler, Michael J. Black

But, even with a better shape model, the problem of regressing dog shape from an image is still challenging because we lack paired images with 3D ground truth.

Fish sounds: towards the evaluation of marine acoustic biodiversity through data-driven audio source separation

no code implementations13 Jan 2022 Michele Mancusi, Nicola Zonca, Emanuele Rodolà, Silvia Zuffi

Moreover, one of the causes of biodiversity loss is sound pollution; in data obtained from regions with loud anthropic noise, it is hard to separate the artificial from the fish sound manually.

Audio Source Separation

Three-D Safari: Learning to Estimate Zebra Pose, Shape, and Texture from Images "In the Wild"

1 code implementation ICCV 2019 Silvia Zuffi, Angjoo Kanazawa, Tanya Berger-Wolf, Michael J. Black

In contrast to research on human pose, shape and texture estimation, training data for endangered species is limited, the animals are in complex natural scenes with occlusion, they are naturally camouflaged, travel in herds, and look similar to each other.

Pose Estimation Texture Synthesis

Lions and Tigers and Bears: Capturing Non-Rigid, 3D, Articulated Shape From Images

no code implementations CVPR 2018 Silvia Zuffi, Angjoo Kanazawa, Michael J. Black

Animals are widespread in nature and the analysis of their shape and motion is important in many fields and industries.

3D Menagerie: Modeling the 3D shape and pose of animals

no code implementations CVPR 2017 Silvia Zuffi, Angjoo Kanazawa, David Jacobs, Michael J. Black

The best human body models are learned from thousands of 3D scans of people in specific poses, which is infeasible with live animals.

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