Antoine Guédon

Introduction

I am a PhD student in the IMAGINE computer vision team of École des Ponts ParisTech (ENPC) and I am co-advised by Vincent Lepetit (ENPC) and Pascal Monasse (ENPC). I am mostly interested in Image-Based Rendering (IBR) and 3D reconstruction using deep learning approaches. In particular, I worked on developing scalable approaches for simultaneously learning to reconstruct and explore 3D environments. More recently, I have been working on Novel View Synthesis and surface reconstruction in radiance fields. Before that, I studied at the Ecole polytechnique as well as the École normale supérieure Paris-Saclay where I obtained the MVA MS degree.

Publications

Gaussian Frosting: Editable Complex Radiance Fields with Real-Time Rendering

ECCV 2024

Antoine Guédon, Vincent Lepetit

We propose to represent surfaces by a mesh covered with a "Frosting" layer of varying thickness and made of 3D Gaussians. This representation captures both complex volumetric effects created by fuzzy materials such as hair or grass as well as flat surfaces. Built from RGB images only, it can be rendered in real-time and animated using traditional animation tools.
Paper Code (coming soon) BibTeX

                                @article{guedon2024frosting,
                                    title={Gaussian Frosting: Editable Complex Radiance Fields with Real-Time Rendering},
                                    author={Gu{\'e}don, Antoine and Lepetit, Vincent},
                                    journal={ECCV},
                                    year={2024}
                              }

SuGaR: Surface-Aligned Gaussian Splatting for Efficient 3D Mesh Reconstruction and High-Quality Mesh Rendering

CVPR 2024

Antoine Guédon, Vincent Lepetit

We introduce a method that extracts accurate and editable meshes from 3D Gaussian Splatting representations within minutes on a single GPU. This enables easy editing, sculpting, rigging, animating, or relighting of the Gaussians using traditional softwares (Blender, Unity, Unreal Engine, etc.) by manipulating the mesh instead of the Gaussians themselves.
Paper Code BibTeX

                                @article{guedon2023sugar,
                                    title={SuGaR: Surface-Aligned Gaussian Splatting for Efficient 3D Mesh Reconstruction and High-Quality Mesh Rendering},
                                    author={Gu{\'e}don, Antoine and Lepetit, Vincent},
                                    journal={CVPR},
                                    year={2024}
                                }

MACARONS: Mapping And Coverage Anticipation with RGB ONline Self-supervision

CVPR 2023

Antoine Guédon, Tom Monnier, Pascal Monasse, Vincent Lepetit

We introduce a novel method that simultaneously learns to explore new large environments and to reconstruct them in 3D from color images only, in a self-supervised fashion.
Paper Code BibTeX

                                @inproceedings{guedon2023macarons,
                                    title={{MACARONS: Mapping And Coverage Anticipation with RGB ONline Self-supervision}},
                                    author={Gu{\'e}don, Antoine and Monnier, Tom and Monasse, Pascal and Lepetit, Vincent},
                                    booktitle={{CVPR}},
                                    year={2023},
                                }

SCONE: Surface Coverage Optimization in uNknown Environments by Volumetric Integration

NeurIPS 2022 (Spotlight)

Antoine Guédon, Pascal Monasse, Vincent Lepetit

We introduce a novel approach to solve the Next Best View problem for dense 3D reconstruction in unknown environments. Contrary to other learning-based methods, our approach scales to large 3D scenes and handles completely free camera motion at inference.
Paper Code BibTeX

                                @inproceedings{guedon2022scone,
                                    title={{SCONE: Surface Coverage Optimization in Unknown Environments by Volumetric Integration}},
                                    author={Gu{\'e}don, Antoine and Monasse, Pascal and Lepetit, Vincent},
                                    booktitle={{Advances in Neural Information Processing Systems}},
                                    year={2022},
                                  }