Publications de Wenzel Alban Jakob

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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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

Modern rendering systems are confronted with a dauntingly large and growing set of requirements: in their pursuit of realism, physically based techniques must increasingly account for intricate properties of light, such as its spectral composition or polar ...

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 ...

Realistic rendering using discrete reflectance measurements is challenging, because arbitrary directions on the light and view hemispheres are queried at render time, incurring large memory requirements and the need for interpolation. This explains the des ...

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 ...

Physically based spectral rendering has become increasingly important in recent years. However, asset textures in such systems are usually still drawn or acquired as RGB tristimulus values. While a number of RGB to spectrum upsampling techniques are availa ...

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 ...

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 ...

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 ...

The Bidirectional Texture Function (BTF) is a data-driven solution to render materials with complex appearance. A typical capture contains tens of thousands of images of a material sample under varying viewing and lighting conditions. While capable of fait ...

Scattering from specular surfaces produces complex optical effects that are frequently encountered in realistic scenes: intricate caustics due to focused reflection, multiple refraction, and high-frequency glints from specular microstructure. Yet, despite ...

Differentiable rendering has recently opened the door to a number of challenging inverse problems involving photorealistic images, such as computational material design and scattering-aware reconstruction of geometry and materials from photographs. Differe ...

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 ...

This paper proposes a new methodology for measuring the error of unbiased physically based rendering algorithms. The current state of the art includes mean squared error (MSE) based metrics and visual comparisons of equal-time renderings of competing algor ...

Wenzel Alban Jakob

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

Projective Sampling for Differentiable Rendering of Geometry

Recursive Control Variates for Inverse Rendering

Inverse Rendering for PET Scanner Calibration

Unbiased Inverse Volume Rendering with Differential Trackers

Differentiable Signed Distance Function Rendering

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

Mitsuba 2: A Retargetable Forward and Inverse Renderer

Large Steps in Inverse Rendering of Geometry

Unified Neural Encoding of BTFs

A Non-Exponential Transmittance Model for Volumetric Scene Representations

Wide Gamut Spectral Upsampling with Fluorescence

MCMC: Bridging Rendering, Optimization and Generative AI

Solving Inverse PDE Problems using Grid-Free Monte Carlo Estimators

Inverse Rendering for PET Image Reconstruction

Neural BTF Compression and Interpolation

Specular Manifold Sampling for Rendering High-Frequency Caustics and Glints

Reparameterizing Discontinuous Integrands for Differentiable Rendering

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

Quantifying the Error of Light Transport Algorithms