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Garvita Tiwari I am a Ph.D. student at the Real Virtual Humans group, Max Planck Institute for Informatics (MPI-INF), Saarbrücken and Tuebinge AI Center, University of Tuebingen , under the supervision of Prof. Dr. Gerard Pons-Moll. I completed my Master's in Visual Computing from Saarland University in November 2019. I earned my Bachelor's degree in Electronics and Communication Engineering from IIIT-Allahabad in 2016. Before starting my Master's, I worked as a Software Engineer at Infurnia Technologies in Bengaluru, India. My research interests include 3D human modeling, clothing models and dynamics, 3D representation and scene understaing, computer vision for graphics, and geometric deep learning. |
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NRDF: Neural Riemannian Distance Fields for Learning Articulated Pose Priors
Yannan He, Garvita Tiwari, Tolga Birdal, Jan Eric Lenssen, Gerard Pons-Moll CVPR, 2024 project page / arXiv / video / code / bibtex Neural Riemannian Distance Fields (NRDFs), a principled method to learn data-driven priors as subspace of high-dimensional Riemannian manifolds. |
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CloSe: A 3D Clothing Segmentation Dataset and Model
Dimitrije Antić, Garvita Tiwari, Batuhan Ozcomlekci, Riccardo Marin, Gerard Pons-Moll 3DV, 2024 project page / arXiv / code / bibtex We present first model that predicts fine-grained clothing segmentation directly from 3D colored point clouds. |
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Pose-NDF: Modeling Human Pose Manifolds with Neural Distance Fields
Garvita Tiwari, Dimitrije Antić, Jan Eric Lenssen, Nikolaos Sarafianos , Tony Tung, Gerard Pons-Moll ECCV, 2022 Best Paper Honourable Mention project page / arXiv / code / bibtex Pose-NDF learns a manifold of plausible poses as the zero level set of a neural implicit function, extending the idea of modeling implicit surfaces in 3D to the high-dimensional domain SO(3)^K, where a human pose is defined by a single data point, represented by K quaternions. |
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Neural-GIF: Neural Generalized Implicit Functions for Animating People in Clothing
Garvita Tiwari, Nikolaos Sarafianos , Tony Tung, Gerard Pons-Moll ICCV, 2021 project page / arXiv / code / bibtex We present Neural Generalized Implicit Functions (Neural-GIF), to animate people in clothing as a function of body pose. Neural-GIF learns directly from scans, models complex clothing and produces pose-dependent details for realistic animation. |
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SIZER: A Dataset and Model for Parsing 3D Clothing and Learning Size Sensitive 3D Clothing
Garvita Tiwari, Bharat Lal Bhatnagar , Tony Tung, Gerard Pons-Moll ECCV, 2020 Oral Presentation project page / arXiv / code / Data / bibtex We introduce the SIZER dataset of clothing size variation which includes 100 different subjects wearing casual clothing items in various sizes, totaling to approximately 2000 scans. |
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Multi-Garment Net: Learning to Dress 3D People from Images
Bharat Lal Bhatnagar , Garvita Tiwari, Christian Theobalt Gerard Pons-Moll ICCV, 2019 project page / arXiv / code / bibtex Multi-Garment Network (MGN), a method to predict body shape and clothing, layered on top of the SMPL model from a few frames (1-8) of a video. |
Academic Services |
Reviewing
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CVPR(2024, 2032, 2022- Outstanding Reviewer), ICCV (2023,2021), ECCV(2024, 2022), 3DV (2024, 2022, 2021, 2020), Eurographics (2021), SIGGRAPH (2021), SIGGRAPH Asia (2024), UIST (2020), MVA (2021) |
Reviewing
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IEEE Transactions on Visualization and Computer Graphics(2021), Computers & Graphics(2022, 2020), Journal of Systems & Applications in Computer Graphics(2021), PeerJ Computer Science(2021) |
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Source: Jon Barron's webpage |