Clément Jambon 🚴‍♂️

I am currently visiting the 3D Vision Lab of SNU 🇰🇷 for my Master's Thesis supervised by Prof. Young Min Kim and Prof. Olga Sorkine-Hornung. I recently completed a 4.5 months research internship at NVIDIA Research under the supervision of Thomas Müller and Merlin Nimier-David. In Fall 2024, I will join the PhD program of MIT EECS under the supervision of Prof. Mina Konaković Luković.

I am studying at ETH Zürich🇨🇭, where I follow a master of science. Among the Computer Science Department, I am majoring in Visual and Interactive Computing and minoring in Machine Learning. Additionally, I recently completed a postgraduate engineering degree at École polytechnique in Paris 🎓.

In Summer 2022, I had the incredible opportunity to take part in a five-month research adventure at Inria Sophia-Antipolis among the GraphDeco team. Supervised by George Drettakis and kindly advised by Georgios Kopanas, Stavros Diolatzis and Thomas Leimkühler, I mostly focused on point-based neural rendering and Neural Radiance Fields a.k.a. NeRF 🔫. This resulted in a contribution to Neural Point Catacaustics released at SIGGRAPH ASIA 2022 and NeRFshop that I presented in 2023 at I3D 👨‍🏫.

I am interested in Computer Graphics and its connections to machine learning. Most notably, I am currently focusing on high-performance, generalizable, and manipulable neural rendering and generation techniques. Some of my recent interests also include physically-based rendering, generative modeling, natural language processing, formal languages and optimal transport 🖥️.

In my free time, I enjoy hiking on Swiss Korean mountains ⛰️, cycling up (and down) steep hills 🚴, running with a compass and a map 🗺️, swimming in freezing lakes and rivers 🏊🏻, reading books and research papers 📖, watching international movies you've probably never heard of 🎥, and first and foremost talking and socializing 👋. So if you want to chat, I'm your man!

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ETH Zürich
Department of Computer Science
Master of Science
Major in Visual and Interactive Computing - Minor in Machine Learning
September 2022 - current


École polytechnique
Department of Computer Science
Postgraduate engineering degree
Major in Image, Vision and Learning
September 2019 - August 2023


NeRFshop: Interactive Editing of Neural Radiance Fields (I3D 2023)
Clément Jambon, Bernhard Kerbl, Georgios Kopanas, Stavros Diolatzis, Thomas Leimkühler, George Drettakis
NeRFshop is a novel end-to-end method that allows users to interactively select and deform objects through cage-based transformations. Once complete, edits can be collapsed and saved as a portable NeRF representation through a distillation process.
Project page | Paper | Video | Talk | Slides

Neural Point Catacaustics for Novel-View Synthesis of Reflections (SIGGRAPH Asia 2022)
Georgios Kopanas, Thomas Leimkühler, Gilles Reiner, Clément Jambon, George Drettakis
We introduce a new point-based representation to compute Neural Point Catacaustics allowing novel-view synthesis of scenes with curved reflectors, from a set of casually-captured input.
Project page | Paper | Video



Research Intern
Supervisors: Thomas Müller and Merlin Nimier-David
October 2023 - February 2024


Inria - GraphDeco Team
Research Intern
Supervisor: George Drettakis
March 2022 - August 2022


Computer Vision Engineer (Internship)
Supervisor: Thibaud Michel
June 2021 - August 2021


Institute of Technology of Cambodia
Teacher and Research Assistant (Internship)
October 2019 - March 2020


Improved 3D scene reconstruction with diffusion models (ETH Zürich)
Semester project supervised by Silvan Weder among the Computer Vision and Geometry Lab
During 5 months, I investigated large-scale 2D diffusion models in order to perform "neural extrapolations" of partial NeRF scenes. To tackle this problem, I mostly focused on the following state-of-the-art techniques: Feature Fields, Score Distillation Sampling (SDS) and feature-guided conditioning of diffusion models.
Report (71.7 MB) | Low-res report (9.7 MB)

Game Theory for Image Segmentation (ETH Zürich)
For the block course Controversies in Game Theory IX: Cooperative and Non-Cooperative Game Theory, I reproduced results from two previous works and implemented from scratch a segmentation algorithm based on game theory and evolutionary dynamics. Additionally, I investigated the use of DINO features for semantic segmentation.
Code | Report

Computer Graphics 2022: Rendering Competition (ETH Zürich)
Honorable Mention of the jury
For the Computer Graphics 2022 Rendering Competition at ETH Zürich, Marius Debussche and I implemented a path tracer with complex features including spectral rendering, subsurface scattering, an advanced camera model and participating media.