Hello!
I am Benoît, a 4th year PhD student at EPFL’s CvLab, supervised by Prof. Pascal Fua.
My work is focused on finding good representations for 3D surface reconstruction and manipulation with neural networks.
I was a research intern at Microsoft Research in 2021 and Meta Reality Labs in 2022.
Publications
(full list on scholar)
DrapeNet: Garment Generation and Self-Supervised Draping
Ren Li*, Luca De Luigi*, Benoit Guillard, Mathieu Salzmann, Pascal Fua ; at CVPR 2023 ( * indicates equal contributions)
We use MeshUDF as a learned parameterization of garments, and learn to drape them without supervision - in the manner of SNUG, but with a single network for a whole category.
DIG: Draping Implicit Garment over the Human Body
Ren Li, Benoit Guillard, Edoardo Remelli, Pascal Fua ; at ACCV 2022 (Oral)
Reconstructing and draping garments over a parametric body model, with neural network trained to avoid collisions.
Learning to Simulate Realistic LiDARs
Benoit Guillard, Sai Vemprala, Jayesh K. Gupta, Ondrej Miksik, Vibhav Vineet, Pascal Fua, Ashish Kapoor ; at IROS 2022
A neural network to simulate how objects interact with LiDARs given their appearance, deployed to a standard driving simulator.
MeshUDF: Fast and Differentiable Meshing of Unsigned Distance Field Networks
Benoit Guillard, Federico Stella, Pascal Fua ; at ECCV 2022
An extension of Marching Cubes to mesh non-watertight surfaces, applied the output of Unsigned Distance Field networks. We also derive gradients for the reconstructed vertex positions wrt. the UDF field.
Sketch2Mesh: Reconstructing and Editing 3D Shapes from Sketches
Benoit Guillard*, Edoardo Remelli*, Pierre Yvernay, Pascal Fua ; at ICCV 2021 ( * indicates equal contributions)
A deep learning based pipeline to reconstruct and locally edit 3D shapes from sketches.
UCLID-Net: Single View Reconstruction in Object Space
Benoit Guillard, Edoardo Remelli, Pascal Fua ; at NeurIPS 2020
A network architecture mixing 3D convolutions and local surface patches for reconstructing object from a single image.
Past, unpublished work
AnalogNet: Convolutional Neural Network Inference on Analog Focal Plane Sensor Processors
Matthew Z Wong*, Benoit Guillard*, Riku Murai, Sajad Saeedi, Paul Kelly ( * indicates equal contributions)
A low-level and super lightweight CNN implementation running directly on the analog light sensor of a special camera, SCAMP5.
Academic services
I was a reviewer for CVPR (2022 best reviewer award), ICCV, ECCV, ACCV, NeurIPS (2022 top reviewer), ICLR, ICML, SIGGRAPH, SIGGRAPH Asia, C&G, WACV, Eurographics.