19 citations · 20 across the 3 of their papers we have counts for
5 papers
From Phase to Phenomenon: Self-Supervised Learning of Subsurface Scattering with Minimal Phase-shift Inputs
Arjun Majumdar, Raphael Braun, Andreas Engelhardt +1
We propose a self-supervised pretraining framework for learning sub-surface scattering (SSS) light transport representations from minimal input. Our method leverages a stereo proje…
Subsurface Scattering for 3D Gaussian Splatting
Jan-Niklas Dihlmann, Arjun Majumdar, Andreas Engelhardt +2
3D reconstruction and relighting of objects made from scattering materials present a significant challenge due to the complex light transport beneath the surface. 3D Gaussian Splat…
CANDID: Correspondence AligNment for Deep-burst Image Denoising
Arijit Mallick, Raphael Braun, Hendrik PA Lensch
With the advent of mobile phone photography and point-and-shoot cameras, deep-burst imaging is widely used for a number of photographic effects such as depth of field, super-resolu…
Neural-PIL: Neural Pre-Integrated Lighting for Reflectance Decomposition
Mark Boss, Varun Jampani, Raphael Braun +3
Decomposing a scene into its shape, reflectance and illumination is a fundamental problem in computer vision and graphics. Neural approaches such as NeRF have achieved remarkable s…
NeRD: Neural Reflectance Decomposition from Image Collections
Mark Boss, Raphael Braun, Varun Jampani +3
Decomposing a scene into its shape, reflectance, and illumination is a challenging but important problem in computer vision and graphics. This problem is inherently more challengin…