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20202025
most citedNeural Reflectance Fields for Appearance Acquisition

110 citations · 228 across the 7 of their papers we have counts for

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5 papers · 1 filter

cs.CV2025

IntrinsicWeather: Controllable Weather Editing in Intrinsic Space

Yixin Zhu, Zuo-Liang Zhu, Jian Yang +3

We present IntrinsicWeather, a diffusion-based framework for controllable weather editing in intrinsic space. Our framework includes two components based on diffusion priors: an in…

cs.CV2021★ 3 cited

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…

cs.CV2020★ 108 cited

MaterialGAN: Reflectance Capture using a Generative SVBRDF Model

Yu Guo, Cameron Smith, Miloš Hašan +2

We address the problem of reconstructing spatially-varying BRDFs from a small set of image measurements. This is a fundamentally under-constrained problem, and previous work has re…

cs.CV2020★ 110 cited

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…

cs.CV2020★ 6 cited

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…