no code implementations • 1 Apr 2024 • Armand Comas-Massagué, Di Qiu, Menglei Chai, Marcel Bühler, Amit Raj, Ruiqi Gao, Qiangeng Xu, Mark Matthews, Paulo Gotardo, Octavia Camps, Sergio Orts-Escolano, Thabo Beeler
We introduce a novel framework for 3D human avatar generation and personalization, leveraging text prompts to enhance user engagement and customization.
no code implementations • 27 Jan 2024 • Lingchen Yang, Gaspard Zoss, Prashanth Chandran, Paulo Gotardo, Markus Gross, Barbara Solenthaler, Eftychios Sifakis, Derek Bradley
At the core, we present a framework for learning implicit physics-based actuations for multiple subjects simultaneously, trained on a few arbitrary performance capture sequences from a small set of identities.
no code implementations • 30 Oct 2023 • Christopher Otto, Prashanth Chandran, Gaspard Zoss, Markus Gross, Paulo Gotardo, Derek Bradley
In this work we propose a new loss function for monocular face capture, inspired by how humans would perceive the quality of a 3D face reconstruction given a particular image.
Ranked #7 on 3D Face Reconstruction on REALY (side-view)
no code implementations • ICCV 2023 • Yingyan Xu, Gaspard Zoss, Prashanth Chandran, Markus Gross, Derek Bradley, Paulo Gotardo
Recent work on radiance fields and volumetric inverse rendering (e. g., NeRFs) has provided excellent results in building data-driven models of real scenes for novel view synthesis with high photorealism.
no code implementations • CVPR 2023 • Prashanth Chandran, Gaspard Zoss, Paulo Gotardo, Derek Bradley
Neural networks for facial landmark detection are notoriously limited to a fixed set of landmarks in a dedicated layout, which must be specified at training time.
2 code implementations • CVPR 2021 • Prashanth Chandran, Gaspard Zoss, Paulo Gotardo, Markus Gross, Derek Bradley
Style transfer between images is an artistic application of CNNs, where the 'style' of one image is transferred onto another image while preserving the latter's content.