Frédéric Fortier-Chouinard

I am pursuing a PhD in Electrical Engineering at Université Laval, under the supervision of Prof. Jean-François Lalonde, funded by an NSERC research scholarship. My research focuses on adding precise physics-based controls to diffusion models, in particular for the task of object compositing and lighting control.

Recently, I had the chance to do an internship at Adobe Research, working with Yannick Hold-Geoffroy, Matheus Gadelha and Valentin Deschaintre.

Previously, I collaborated with Mathieu Garon from Depix and Anand Bhattad on developing new object compositing and lighting control methods.

I obtained my Bachelor's in Computer Engineering at Université Laval. I pursued an exchange semester in 2022 at EPFL, Switzerland. During my undergrad, I completed three internships where I worked on high-performance computing (HPC) software at Calcul Québec, integrated a machine-learning pipeline in the cloud at Dimonoff, and researched GAN-based high-resolution inpainting methods with Prof. Lalonde.

CV  /  Email  /  GitHub  /  Google Scholar  /  LinkedIn

profile photo

Research

I'm interested in computer vision, machine learning, graphics, and image generation models.

project image

SpotLight: Shadow-Guided Object Relighting via Diffusion


Frédéric Fortier-Chouinard, Zitian Zhang, Louis-Etienne Messier, Mathieu Garon, Anand Bhattad, Jean-François Lalonde
3DV 2026
arxiv / website /

SpotLight allows precise local lighting control by specifying the desired shadows of the inserted object. This approach accurately reshades the object and properly harmonizes the object with the target background, without any training.
project image

ZeroComp: Zero-shot Object Compositing from Image Intrinsics via Diffusion


Zitian Zhang, Frédéric Fortier-Chouinard, Mathieu Garon, Anand Bhattad, Jean-François Lalonde
WACV 2025
arxiv / code / poster / website /

Zero-shot 3D object compositing approach that does not require paired composite-scene images during training and can be easily extended to 2D object compositing and material editing.
project image

PanDORA: Casual HDR Radiance Acquisition for Indoor Scenes


Mohammad Reza Karimi Dastjerdi, Dominique Tanguay-Gaudreau, Frédéric Fortier-Chouinard, Yannick Hold-Geoffroy, Claude Demers, Nima Kalantari, Jean-François Lalonde
arXiv 2024
arxiv / website /

PanDORA is a system that allows for HDR capture of indoor scenes using a simple capture device, composed of two cameras. The captured frames are fed two a NeRF-based algorithm that reconstructs the scene’s high dynamic range, allowing applications such as virtual object relighting.



Other Projects
project image

CinematicSpark.com


startup
2025

CinematicSpark is an easy-to-use web application for creating personnalized images of a subject (e.g. a person) using only a handful of low-quality photos as input. It brings cutting-edge techniques in personnalized image generation in the hands of beginner users.
project image

MC Hub


internship
2020
code /

Open source web application for managing cloud high-performance computing (HPC) clusters that I developed during my internship at Calcul Québec. MC Hub is still maintained and used for training HPC users.

Design and source code from Jon Barron's and Leonid Keselman's websites.