Publications (11)
ReLi3D: Relightable Multi-view 3D Reconstruction with Disentangled Illumination
Jan-Niklas Dihlmann, Mark Boss, Simon Donne +3
Reconstructing 3D assets from images has long required separate pipelines for geometry reconstruction, material estimation, and illumination recovery, each with distinct limitation…
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…
ReSWD: ReSTIR'd, not shaken. Combining Reservoir Sampling and Sliced Wasserstein Distance for Variance Reduction
Mark Boss, Andreas Engelhardt, Simon Donné +1
Distribution matching is central to many vision and graphics tasks, where the widely used Wasserstein distance is too costly to compute for high dimensional distributions. The Slic…
Arbor: Explicit Geometric Conditioning for Controllable 3D Asset Generation
Jan-Niklas Dihlmann, Andreas Engelhardt, Simon Donne +2
Text and image conditioned 3D models now generate convincing assets, but they still offer little direct control over the space an object should occupy or avoid. In authoring, this…
SHINOBI: Shape and Illumination using Neural Object Decomposition via BRDF Optimization In-the-wild
Andreas Engelhardt, Amit Raj, Mark Boss +8
We present SHINOBI, an end-to-end framework for the reconstruction of shape, material, and illumination from object images captured with varying lighting, pose, and background. Inv…
SAMURAI: Shape And Material from Unconstrained Real-world Arbitrary Image collections
Mark Boss, Andreas Engelhardt, Abhishek Kar +5
Inverse rendering of an object under entirely unknown capture conditions is a fundamental challenge in computer vision and graphics. Neural approaches such as NeRF have achieved ph…
NAVI: Category-Agnostic Image Collections with High-Quality 3D Shape and Pose Annotations
Varun Jampani, Kevis-Kokitsi Maninis, Andreas Engelhardt +13
Recent advances in neural reconstruction enable high-quality 3D object reconstruction from casually captured image collections. Current techniques mostly analyze their progress on…
SIGNeRF: Scene Integrated Generation for Neural Radiance Fields
Jan-Niklas Dihlmann, Andreas Engelhardt, Hendrik Lensch
Advances in image diffusion models have recently led to notable improvements in the generation of high-quality images. In combination with Neural Radiance Fields (NeRFs), they enab…
SViM3D: Stable Video Material Diffusion for Single Image 3D Generation
Andreas Engelhardt, Mark Boss, Vikram Voleti +3
We present Stable Video Materials 3D (SViM3D), a framework to predict multi-view consistent physically based rendering (PBR) materials, given a single image. Recently, video diffus…
3D Congealing: 3D-Aware Image Alignment in the Wild
Yunzhi Zhang, Zizhang Li, Amit Raj +5
We propose 3D Congealing, a novel problem of 3D-aware alignment for 2D images capturing semantically similar objects. Given a collection of unlabeled Internet images, our goal is t…