204 citations · 703 across the 41 of their papers we have counts for
21 papers · 1 filter
Volumetric Inverse Rendering via Neural Radiative Transfer
Ntumba Elie Nsampi, Adarsh Djeacoumar, Hans-Peter Seidel +2
Volumetric inverse rendering seeks to recover the optical properties of participating media from images. Existing approaches either rely on differentiable stochastic light transpor…
Bracket Diffusion: HDR Image Generation by Consistent LDR Denoising
Mojtaba Bemana, Thomas Leimkühler, Karol Myszkowski +2
We demonstrate generating HDR images using the concerted action of multiple black-box, pre-trained LDR image diffusion models. Relying on a pre-trained LDR generative diffusion mod…
Patternshop: Editing Point Patterns by Image Manipulation
Xingchang Huang, Tobias Ritschel, Hans-Peter Seidel +2
Point patterns are characterized by their density and correlation. While spatial variation of density is well-understood, analysis and synthesis of spatially-varying correlation is…
Learning to Rasterize Differentiably
Chenghao Wu, Hamila Mailee, Zahra Montazeri +1
Differentiable rasterization changes the standard formulation of primitive rasterization -- by enabling gradient flow from a pixel to its underlying triangles -- using distribution…
Learning to Learn and Sample BRDFs
Chen Liu, Michael Fischer, Tobias Ritschel
We propose a method to accelerate the joint process of physically acquiring and learning neural Bi-directional Reflectance Distribution Function (BRDF) models. While BRDF learning…
OutCast: Outdoor Single-image Relighting with Cast Shadows
David Griffiths, Tobias Ritschel, Julien Philip
We propose a relighting method for outdoor images. Our method mainly focuses on predicting cast shadows in arbitrary novel lighting directions from a single image while also accoun…
Metappearance: Meta-Learning for Visual Appearance Reproduction
Michael Fischer, Tobias Ritschel
There currently exist two main approaches to reproducing visual appearance using Machine Learning (ML): The first is training models that generalize over different instances of a p…
Eikonal Fields for Refractive Novel-View Synthesis
Mojtaba Bemana, Karol Myszkowski, Jeppe Revall Frisvad +2
We tackle the problem of generating novel-view images from collections of 2D images showing refractive and reflective objects. Current solutions assume opaque or transparent light…
Metameric Varifocal Holography
David R. Walton, Koray Kavaklı, Rafael Kuffner dos Anjos +6
Computer-Generated Holography (CGH) offers the potential for genuine, high-quality three-dimensional visuals. However, fulfilling this potential remains a practical challenge due t…
Blue Noise Plots
Christian van Onzenoodt, Gurprit Singh, Timo Ropinski +1
We propose Blue Noise Plots, two-dimensional dot plots that depict data points of univariate data sets. While often one-dimensional strip plots are used to depict such data, one of…
Generative Modelling of BRDF Textures from Flash Images
Philipp Henzler, Valentin Deschaintre, Niloy J. Mitra +1
We learn a latent space for easy capture, consistent interpolation, and efficient reproduction of visual material appearance. When users provide a photo of a stationary natural mat…
Neural BRDF Representation and Importance Sampling
Alejandro Sztrajman, Gilles Rainer, Tobias Ritschel +1
Controlled capture of real-world material appearance yields tabulated sets of highly realistic reflectance data. In practice, however, its high memory footprint requires compressin…
Neural View-Interpolation for Sparse Light Field Video
Mojtaba Bemana, Karol Myszkowski, Hans-Peter Seidel +1
We suggest representing light field (LF) videos as "one-off" neural networks (NN), i.e., a learned mapping from view-plus-time coordinates to high-resolution color values, trained…
Learning to Predict Image-based Rendering Artifacts with Respect to a Hidden Reference Image
Mojtaba Bemana, Joachim Keinert, Karol Myszkowski +4
Image metrics predict the perceived per-pixel difference between a reference image and its degraded (e. g., re-rendered) version. In several important applications, the reference i…
Deep-learning the Latent Space of Light Transport
Pedro Hermosilla, Sebastian Maisch, Tobias Ritschel +1
We suggest a method to directly deep-learn light transport, i. e., the mapping from a 3D geometry-illumination-material configuration to a shaded 2D image. While many previous lear…
End-to-end Sampling Patterns
Thomas Leimkühler, Gurprit Singh, Karol Myszkowski +2
Sample patterns have many uses in Computer Graphics, ranging from procedural object placement over Monte Carlo image synthesis to non-photorealistic depiction. Their properties suc…
Perceptual Rasterization for Head-mounted Display Image Synthesis
Tobias Ritschel, Sebastian Friston, Anthony Steed
We suggest a rasterization pipeline tailored towards the need of head-mounted displays (HMD), where latency and field-of-view requirements pose new challenges beyond those of tradi…
Joint Material and Illumination Estimation from Photo Sets in the Wild
Tuanfeng Y. Wang, Tobias Ritschel, Niloy J. Mitra
Faithful manipulation of shape, material, and illumination in 2D Internet images would greatly benefit from a reliable factorization of appearance into material (i.e., diffuse and…
Single-image Tomography: 3D Volumes from 2D Cranial X-Rays
Philipp Henzler, Volker Rasche, Timo Ropinski +1
As many different 3D volumes could produce the same 2D x-ray image, inverting this process is challenging. We show that recent deep learning-based convolutional neural networks can…
Plausible Shading Decomposition For Layered Photo Retouching
Carlo Innamorati, Tobias Ritschel, Tim Weyrich +1
Photographers routinely compose multiple manipulated photos of the same scene (layers) into a single image, which is better than any individual photo could be alone. Similarly, 3D…
Deep Shading: Convolutional Neural Networks for Screen-Space Shading
Oliver Nalbach, Elena Arabadzhiyska, Dushyant Mehta +2
In computer vision, convolutional neural networks (CNNs) have recently achieved new levels of performance for several inverse problems where RGB pixel appearance is mapped to attri…