Publications de Wenzel Alban Jakob

The Mokume Dataset and Inverse Modeling of Solid Wood Textures

We present the Mokume dataset for solid wood texturing consisting of 190 cube-shaped samples of various hard and softwood species documented by high-resolution exterior photographs, annual ring annotations, and volumetric computed tomography (CT) scans. A ...

Association for Computing Machinery (ACM)2025

Radiance Surfaces: Optimizing Surface Representations with a 5D Radiance Field Loss

Nicolas Julien Roussel, Merlin Eléazar Nimier-David, Wenzel Alban Jakob, Tizian Lucien Zeltner

We present a fast and simple technique to convert images into a radiance surface-based scene representation. Building on existing radiance volume reconstruction algorithms, we introduce a subtle yet impactful modification of the loss function requiring cha ...

ACM2025

A Simple Approach to Differentiable Rendering of SDFs

Wenzel Alban Jakob

We present a simple algorithm for differentiable rendering of surfaces represented by Signed Distance Fields (SDF), which makes it easy to integrate rendering into gradient-based optimization pipelines. To tackle visibility-related derivatives that make re ...

ACM Association for Computing Machinery2024

MCMC: Bridging Rendering, Optimization and Generative AI

Wenzel Alban Jakob

Generative artificial intelligence (AI) has made unprecedented advances in vision language models over the past two years. These advances are largely due to diffusion-based generative models, which are very stable and simple to train. These diffusion model ...

Association for Computing Machinery, Inc2024

Prism-PET II: Second prototype of the TOF-DOI Prism-PET brain scanner with tapered crystals and inverse rendering reconstruction

Wenzel Alban Jakob, Baptiste Alexandre Marie Philippe Claude Nicolet

Accurate PET quantification of tracer uptake in small brain structures is confounded by low sensitivity and the partial volume effect (PVE) caused by limited spatial resolution. In this study, we present the second prototype of the Prism-PET brain scanner ...

IEEE2024

Inverse Rendering for Tomographic Volumetric Additive Manufacturing

Christophe Moser, Wenzel Alban Jakob, Jorge Andres Madrid Wolff, Baptiste Alexandre Marie Philippe Claude Nicolet, Felix Wechsler

Tomographic Volumetric Additive Manufacturing (TVAM) is an emerging 3D printing technology that can create complex objects in under a minute. The key idea is to project intense light patterns onto a rotating vial of photo-sensitive resin, causing polymeriz ...

2024

Inverse Rendering for PET Image Reconstruction

Wenzel Alban Jakob, Baptiste Alexandre Marie Philippe Claude Nicolet

Differentiable rendering (DR) is an emerging field that facilitates the calculation and propagation of gradients of 3D objects through images. In contrast to deep neural networks (DNNs), which generally lack the understanding of 3D objects that form the im ...

IEEE2024

Solving Inverse PDE Problems using Grid-Free Monte Carlo Estimators

Wenzel Alban Jakob

Partial differential equations can model diverse physical phenomena including heat diffusion, incompressible flows, and electrostatic potentials. Given a description of an object's boundary and interior, traditional methods solve such PDEs by densely meshi ...

2024

Inverse Rendering for PET Scanner Calibration

Yu Lin, Wenzel Alban Jakob

The significant degradation of reconstructed image resolution and the presence of apparent artifacts can result from sub-millimetric misalignment of scanner configuration in highspatial resolution positron emission tomography (PET) systems. Therefore, ensu ...

IEEE2024

Projective Sampling for Differentiable Rendering of Geometry

Nicolas Julien Roussel, Wenzel Alban Jakob

Discontinuous visibility changes at object boundaries remain a persistent source of difficulty in the area of differentiable rendering. Left untreated, they bias computed gradients so severely that even basic optimization tasks fail.|Prior path-space metho ...

2023

Recursive Control Variates for Inverse Rendering

Wenzel Alban Jakob, Baptiste Alexandre Marie Philippe Claude Nicolet

We present a method for reducing errors-variance and bias-in physically based differentiable rendering (PBDR). Typical applications of PBDR repeatedly render a scene as part of an optimization loop involving gradient descent. The actual change introduced b ...

2023

Dr.Jit: A Just-In-Time Compiler for Differentiable Rendering

Sébastien Nicolas Speierer, Nicolas Julien Roussel, Wenzel Alban Jakob, Delio Aleardo Vicini

Dr.Jit is a new just-in-time compiler for physically based rendering and its derivative. Dr.Jit expedites research on these topics in two ways: first, it traces high-level simulation code (e.g., written in Python) and aggressively simplifies and specialize ...

2022

Differentiable Signed Distance Function Rendering

Sébastien Nicolas Speierer, Wenzel Alban Jakob, Delio Aleardo Vicini

Physically-based differentiable rendering has recently emerged as an attractive new technique for solving inverse problems that recover complete 3D scene representations from images. The inversion of shape parameters is of particular interest but also pose ...

ASSOC COMPUTING MACHINERY2022

Unbiased Inverse Volume Rendering with Differential Trackers

Merlin Eléazar Nimier-David, Wenzel Alban Jakob

Volumetric representations are popular in inverse rendering because they have a simple parameterization, are smoothly varying, and transparently handle topology changes. However, incorporating the full volumetric transport of light is costly and challengin ...

ASSOC COMPUTING MACHINERY2022

A Non-Exponential Transmittance Model for Volumetric Scene Representations

Wenzel Alban Jakob, Delio Aleardo Vicini

We introduce a novel transmittance model to improve the volumetric representation of 3D scenes. The model can represent opaque surfaces in the volumetric light transport framework. Volumetric representations are useful for complex scenes, and become increa ...

ASSOC COMPUTING MACHINERY2021

Wide-Depth-Range 6D Object Pose Estimation in Space

Pascal Fua, Mathieu Salzmann, Wenzel Alban Jakob, Yinlin Hu

6D pose estimation in space poses unique challenges that are not commonly encountered in the terrestrial setting. One of the most striking differences is the lack of atmospheric scattering, allowing objects to be visible from a great distance while complic ...

IEEE2021

Path Replay Backpropagation: Differentiating Light Paths using Constant Memory and Linear Time

Sébastien Nicolas Speierer, Wenzel Alban Jakob, Delio Aleardo Vicini

Differentiable physically-based rendering has become an indispensable tool for solving inverse problems involving light. Most applications in this area jointly optimize a large set of scene parameters to minimize an objective function, in which case revers ...

ASSOC COMPUTING MACHINERY2021

Large Steps in Inverse Rendering of Geometry

Wenzel Alban Jakob, Baptiste Alexandre Marie Philippe Claude Nicolet

Inverse reconstruction from images is a central problem in many scientific and engineering disciplines. Recent progress on differentiable rendering has led to methods that can efficiently differentiate the full process of image formation with respect to mi ...

ASSOC COMPUTING MACHINERY2021

Differentiable inverse rendering based on radiative backpropagation

Merlin Eléazar Nimier-David, Wenzel Alban Jakob

A computer-implemented inverse rendering method is provided. The method comprises: computing an adjoint image by differentiating an objective function that evaluates the quality of a rendered image, image elements of the adjoint image encoding the sensitiv ...

2021

Monte Carlo Estimators for Differential Light Transport

Sébastien Nicolas Speierer, Wenzel Alban Jakob, Tizian Lucien Zeltner

Physically based differentiable rendering algorithms propagate derivatives through realistic light transport simulations and have applications in diverse areas including inverse reconstruction and machine learning. Recent progress has led to unbiased metho ...

ASSOC COMPUTING MACHINERY2021