Baptiste GENEST

@baptiste-genest.bsky.social

Applied math and Geometry lover, discrete geometer wannabe. PhD Student at LIRIS. he/him baptiste-genest.github.io

At the end of my internship at Adobe, we could not release code for numerous reasons. But I thought that the pseudo-code in the paper would be enough for anyone to re-implement it! I was wrong 🫠 @arezdev.de contacted me a week ago, asking why his implementation did not work...

Baptiste GENEST@baptiste-genest.bsky.social · last yr.

Implicit surfaces are great, but if you are not Inigo Quilez, it's really hard to control how they look... That's why I'm really proud to annonce our Eurographics 2025 paper: "Implicit UVs: Real-time semi-global parameterization of implicit surfaces".

I recently completed my PhD thesis, where I developed algorithms for making geometric inferences from imperfect data (i.e. incomplete and inaccurate observations/representations of shapes, like broken meshes or point clouds). A thread 🧵:

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When dealing with noisy and/or partial inputs to describe a shape, the standard approach in geometry processing is to reconstruct a clean implicit surface first, and to do geometry on it. But why this one in particular? What about all the other surfaces that would have been coherent with the input?

For those interested in normalized gradient methods and optimal transport: I introduce a new class of "spectral" Wasserstein distances for which spectrally normalized gradient descent (Muon but without momentum and small step size ...) is a spectral-W gradient flow: arxiv.org/abs/2604.04891

Muon Dynamics as a Spectral Wasserstein Flow

Gradient normalization is central in deep-learning optimization because it stabilizes training and reduces sensitivity to scale. For deep architectures, parameters are naturally grouped into matrices ...

arxiv.org

Super happy and honored to share that our paper "BSP-OT: Sparse transport plans between discrete measures in log-linear time" won a *Best paper award* at SIGGRAPH Asia 2025! If you are here, come see my presentation about this work Wednesday afternoon! Many thanks to the award committee!

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Baptiste GENEST@baptiste-genest.bsky.social · 10mo ago

Computing the exact bijection of the optimal transport (OT) problem between very large point sets is completely untractable… In our SIGGRAPH Asia 2025 paper: “BSP-OT: Sparse transport plans between discrete measures in log-linear time” we get one with typically 1% of error in a few seconds on CPU!

Computing the exact bijection of the optimal transport (OT) problem between very large point sets is completely untractable… In our SIGGRAPH Asia 2025 paper: “BSP-OT: Sparse transport plans between discrete measures in log-linear time” we get one with typically 1% of error in a few seconds on CPU!

Vous avez sûrement déjà lu que la climatisation aggrave les canicules car l’air chaud rejeté à l’extérieur augmenterait la température des villes de 2 à 3°C. Vérifions ce que disent vraiment les études scientifiques à ce sujet 🧑‍🔬 (lisez jusqu’au bout, car vous allez être 🤯🤯 à la fin) #Thread ⬇️⬇️

Carte de Paris simulation îlot de chaleur

📜 New SIGGRAPH 2025 paper 🎉 ❔How to compute bounding volumes for procedural Signed Distance Fields (SDFs)? This is not so trivial! 💡We propose a simple method called Sphere Carving. It extracts (convex) bounding volumes around SDFs, requires very few evaluations, and is GPU compatible.

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