1 citations · 2 across the 13 of their papers we have counts for
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InvSplat: Inverse Feed-Forward Scene Splatting
Polina Karpikova, Wenjing Bian, Haofei Xu +2
Inverse rendering aims to recover both 3D geometry and physically meaningful material properties from images, enabling applications such as relighting and novel view synthesis. Opt…
AEGIR: Modeling Area Emitters for Indoor Inverse Rendering using Gaussian Splatting
Mohamed Shawky Sabae, Philipp Langsteiner, Jan-Niklas Dihlmann +1
Inverse rendering requires separating illumination from surface materials, which is highly ambiguous due to their tight coupling in observed images. While Gaussian Splatting is eff…
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…
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…
Neural Acquisition & Representation of Subsurface Scattering
Arjun Majumdar, Raphael Braun, Hendrik Lensch
We present a method to acquire and estimate the sub-surface scattering properties of light transport at a highly detailed level by learning the pixel footprint response at each poi…
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…