HEIndividual fellowship2023–2024

CoMBo · Correspondence through Millions Bodies: a large-scale, functional, and implicit data-driven method for 3D Humans matching

Horizon Europe — Marie Skłodowska-Curie Actions

Duration
2023-07-01 → 2024-07-31
EU contribution
€86,924
Participants
1
Scheme
HORIZON-TMA-MSCA-PF-EF

Lines connect the coordinator with its partners.

Results in brief

Correspondence through Millions Bodies: a large-scale, functional, and implicit data-driven method for 3D Humans matching

Geometry surrounds our lives, and we recognize ourselves as part of the 3D world. We inherently interact and reason about it, while its formalization is challenging and has tickled scholars since the dawn of civilization. The advent of computers and the study of Geometry Processing opened dramatic advancements and possibilities, like simulated surgeons' operations or whole digital universes. Among all the physical entities, the human bodies play a central role. Modern technologies can acquire, digitalize, and imitate human appearance at a stage that is indistinguishable from reality. Interest in Virtual Humans is growing fast in public opinion and several scientific and economic fields, from entertainment to medicine, social sciences to ergonomics. The market of Virtual Avatars has an estimated value of around USD 10 billion and is expected to reach more than USD 520 billion in 2030. However, our understanding can only be complete with tools to establish analogies: what is similar, what is different, or, namely, what is in correspondence. Finding such connections between human geometry is the key enabler for several downstream applications such as virtual try-on, texture transfer, or performing anthropometric statistics. Computer Vision and Graphics have studied the problem intensely since its fundamental and applicative relevance. Still, no method has affirmed itself as a robust and flexible standard to obtain robust and precise 3D correspondence across different humans. Noise, garments, objects, or partiality often pose challenges that require ad-hoc strategies. The CoMBo (Correspondence through Millions Bodies) project aims to fill this gap by combining multiple techniques: relying on a vast human dataset, exploiting flexible geometrical representation, and developing a novel data-driven framework cable to handle this comprehensive set of challenges. CoMBo will produce substantial scientific, economic, and social impacts in this strategic field, carrying an intense outreach to a broad audience, informing on bodies digitalization process and the importance of fair representation of the human experience in this fast-changing technology.

Data: CORDIS, © European Union

Project objective

Interest in Virtual Humans is growing fast in public opinion and in several scientific and economic fields, from entertainment to medicine, from social sciences to ergonomics. The market of Virtual Avatars has a value estimated around USD 10 Billion and is expected to reach more than USD 520 Billion in 2030. To investigate, learn from, and represent fairly the wide variety of human experiences, tools to establish analogies or, namely, correspondence between them are required. Computer Vision and Graphics studied the problem intensely, but so far, no method has affirmed itself as a robust and flexible standard. This ambitious action aims to fill this gap, starting from three observations: 1) few methods rely on implicit representations, despite their flexibility and resilience; 2) especially, well-studied theoretical methods capable of strong regularizations have never been applied to these representations; 3) no method takes full advantage of large-scale datasets. This action will combine these aspects, following a roadmap with three major scientific objectives:a) Collecting dataset of 10 Million bodies with different properties, encoded as implicit representation, equipped with a ground-truth correspondence;b) Developing a novel data-driven framework based on Functional Maps theory for implicit representations;c) Deploying a large-scale neural network for 3D Human Correspondence beneficiary of the previous bullets, usable in real-world scenariosThis MSCA will produce substantial scientific, economic, and social impacts in this strategic field thanks to the interdisciplinary union of mathematical tools for functional analysis, the latest advances in deep learning, and domain knowledge of human bodies. This action will carry an intense outreach to a broad audience, informing on bodies digitalization process and the importance of fair representation of the human experience in this fast-changing technology.

Original text from CORDIS.

Participants

  • EBERHARD KARLS UNIVERSITAET TUEBINGEN · TuebingenCoordinatorGermany

Links

Data: CORDIS, © European Union