no code implementations • 11 Jan 2024 • Partha Ghosh, Soubhik Sanyal, Cordelia Schmid, Bernhard Schölkopf
To capture these dependencies, our approach incorporates a hybrid explicit-implicit tri-plane representation inspired by 3D-aware generative frameworks developed for three-dimensional object representation and employs a singular latent code to model an entire video sequence.
no code implementations • 22 Dec 2023 • Mirela Ostrek, Soubhik Sanyal, Carol O'Sullivan, Michael J. Black, Justus Thies
The method is analyzed quantitatively and qualitatively, and we show that ESP outperforms state-of-the-art on the task of contextual full-body generation.
no code implementations • 21 Aug 2023 • Soubhik Sanyal, Partha Ghosh, Jinlong Yang, Michael J. Black, Justus Thies, Timo Bolkart
We present SCULPT, a novel 3D generative model for clothed and textured 3D meshes of humans.
no code implementations • ICCV 2021 • Soubhik Sanyal, Alex Vorobiov, Timo Bolkart, Matthew Loper, Betty Mohler, Larry Davis, Javier Romero, Michael J. Black
Synthesizing images of a person in novel poses from a single image is a highly ambiguous task.
2 code implementations • CVPR 2019 • Soubhik Sanyal, Timo Bolkart, Haiwen Feng, Michael J. Black
The estimation of 3D face shape from a single image must be robust to variations in lighting, head pose, expression, facial hair, makeup, and occlusions.
2 code implementations • ECCV 2018 • Anurag Ranjan, Timo Bolkart, Soubhik Sanyal, Michael J. Black
To address this, we introduce a versatile model that learns a non-linear representation of a face using spectral convolutions on a mesh surface.
Ranked #4 on Face Alignment on FaceScape
no code implementations • ICCV 2015 • Soubhik Sanyal, Sivaram Prasad Mudunuri, Soma Biswas
The DPFD of images taken from different viewpoints can be directly compared for matching.