110 citations · 130 across the 5 of their papers we have counts for
9 papers
NeuTex: Neural Texture Mapping for Volumetric Neural Rendering
Fanbo Xiang, Zexiang Xu, Miloš Hašan +3
Recent work has demonstrated that volumetric scene representations combined with differentiable volume rendering can enable photo-realistic rendering for challenging scenes that me…
Neural Reflectance Fields for Appearance Acquisition
Sai Bi, Zexiang Xu, Pratul Srinivasan +6
We present Neural Reflectance Fields, a novel deep scene representation that encodes volume density, normal and reflectance properties at any 3D point in a scene using a fully-conn…
Deep Multi Depth Panoramas for View Synthesis
Kai-En Lin, Zexiang Xu, Ben Mildenhall +6
We propose a learning-based approach for novel view synthesis for multi-camera 360 panorama capture rigs. Previous work constructs RGBD panoramas from such data, allowing…
Deep Reflectance Volumes: Relightable Reconstructions from Multi-View Photometric Images
Sai Bi, Zexiang Xu, Kalyan Sunkavalli +4
We present a deep learning approach to reconstruct scene appearance from unstructured images captured under collocated point lighting. At the heart of Deep Reflectance Volumes is a…
Single View Metrology in the Wild
Rui Zhu, Xingyi Yang, Yannick Hold-Geoffroy +4
Most 3D reconstruction methods may only recover scene properties up to a global scale ambiguity. We present a novel approach to single view metrology that can recover the absolute…
Deep Parametric Indoor Lighting Estimation
Marc-André Gardner, Yannick Hold-Geoffroy, Kalyan Sunkavalli +2
We present a method to estimate lighting from a single image of an indoor scene. Previous work has used an environment map representation that does not account for the localized na…