Publications de Ren Li | EPFL Graph Search

Neural Garment Modeling

The digitization of 3D deformable objects remains a significant challenge in computer graphics and vision, particularly in the accurate modeling of garments. Garments exhibit complex shape variability, non-rigid deformations, and frequent self-occlusion, m ...

EPFL2025

Single View Garment Reconstruction Using Diffusion Mapping Via Pattern Coordinates

Pascal Fua, Ren Li, Corentin Camille Marius Dumery

2025

Garment Recovery with Shape and Deformation Priors

Pascal Fua, Benoît Alain René Guillard, Ren Li, Corentin Camille Marius Dumery

While modeling people wearing tight-fitting clothing has made great strides in recent years, loose-fitting clothing remains a challenge. We propose a method that delivers realistic garment models from real-world images, regardless of garment shape or defor ...

2024

Reconstruction of Manipulated Garment with Guided Deformation Prior

Pascal Fua, Ren Li, Zhantao Deng, Corentin Camille Marius Dumery

Modeling the shape of garments has received much attention, but most existing approaches assume the garments to be worn by someone, which constrains the range of shapes they can assume. In this work, we address shape recovery when garments are being manipu ...

2024

DrapeNet: Garment Generation and Self-Supervised Draping

Pascal Fua, Mathieu Salzmann, Benoît Alain René Guillard, Ren Li, Luca De Luigi

Recent approaches to drape garments quickly over arbitrary human bodies leverage self-supervision to eliminate the need for large training sets. However, they are designed to train one network per clothing item, which severely limits their generalization a ...

IEEE2023

ISP: Multi-Layered Garment Draping with Implicit Sewing Patterns

Pascal Fua, Benoît Alain René Guillard, Ren Li

Many approaches to draping individual garments on human body models are realistic, fast, and yield outputs that are differentiable with respect to the body shape on which they are draped. However, they are either unable to handle multi-layered clothing, wh ...

2023

DIG: Draping Implicit Garment over the Human Body

Pascal Fua, Benoît Alain René Guillard, Ren Li, Edoardo Remelli

Existing data-driven methods for draping garments over human bodies, despite being effective, cannot handle garments of arbitrary topology and are typically not end-to-end differentiable. To address these limitations, we propose an end-to-end differentiabl ...

SPRINGER INTERNATIONAL PUBLISHING AG2022