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We propose a scene-level inverse rendering framework that uses multi-view images to decompose the scene into geometry, a SVBRDF, and 3D spatially-varying lighting.
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Ground truth dataset and baseline evaluations for intrinsic image algorithms
Roger Grosse, Micah K Johnson, Edward H Adelson, and William T Freeman · 2009
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Shape and reflectance from natural illumination
Geoffrey Oxholm and Ko Nishino · 2012
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Real shading in unreal engine 4
Brian Karis and Epic Games · 2013
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Intrinsic images in the wild
Sean Bell, Kavita Bala, and Noah Snavely · 2014
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Fully convolutional networks for semantic segmentation
Jonathan Long, Evan Shelhamer, and Trevor Darrell · 2015
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Multi-view inverse rendering under arbitrary illumination and albedo
Kichang Kim, Akihiko Torii, and Masatoshi Okutomi · 2016
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Emptying, refurnishing, and relighting indoor spaces
Edward Zhang, Michael F. Cohen, and Brian Curless · 2016
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Modulating early visual processing by language
Harm De Vries, Florian Strub, Jérémie Mary, Hugo Larochelle, Olivier Pietquin, and Aaron C Courville · 2017
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Learning to predict indoor illumination from a single image
Marc-André Gardner, Kalyan Sunkavalli, Ersin Yumer, Xiaohui Shen, Emiliano Gambaretto, Christian Gagné, and Jean-François Lalonde · 2017
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Intrinsic3D: High-quality 3D reconstruction by joint appearance and geometry optimization with spatially-varying lighting
Robert Maier, Kihwan Kim, Daniel Cremers, Jan Kautz, and Matthias Nießner · 2017
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Single-image svbrdf capture with a rendering-aware deep network
Valentin Deschaintre, Miika Aittala, Fredo Durand, George Drettakis, and Adrien Bousseau · 2018
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Single-image svbrdf capture with a rendering-aware deep network
Valentin Deschaintre, Miika Aittala, Fredo Durand, George Drettakis, and Adrien Bousseau · 2018
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Interiornet: Mega-scale multi-sensor photo-realistic indoor scenes dataset
Wenbin Li, Sajad Saeedi, John McCormac, Ronald Clark, Dimos Tzoumanikas, Qing Ye, Yuzhong Huang, Rui Tang, and Stefan Leutenegger · 2018
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Cgintrinsics: Better intrinsic image decomposition through physically-based rendering
Zhengqi Li and Noah Snavely · 2018
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Materials for masses: Svbrdf acquisition with a single mobile phone image
Zhengqin Li, Kalyan Sunkavalli, and Manmohan Chandraker · 2018
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Learning to reconstruct shape and spatially-varying reflectance from a single image
Zhengqin Li, Zexiang Xu, Ravi Ramamoorthi, Kalyan Sunkavalli, and Manmohan Chandraker · 2018
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Inverse path tracing for joint material and lighting estimation
Dejan Azinovic, Tzu-Mao Li, Anton Kaplanyan, and Matthias Nießner · 2019
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Deep parametric indoor lighting estimation
Marc-André Gardner, Yannick Hold-Geoffroy, Kalyan Sunkavalli, Christian Gagné, and Jean-François Lalonde · 2019
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Fast spatially-varying indoor lighting estimation
Mathieu Garon, Kalyan Sunkavalli, Sunil Hadap, Nathan Carr, and Jean-François Lalonde · 2019
Cited alongside, same era.
Occupancy networks: Learning 3d reconstruction in function space
Nerv: Neural reflectance and visibility fields for relighting and view synthesis
Pratul P Srinivasan, Boyang Deng, Xiuming Zhang, Matthew Tancik, Ben Mildenhall, and Jonathan T Barron · 2021
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Ibrnet: Learning multi-view image-based rendering
Qianqian Wang, Zhicheng Wang, Kyle Genova, Pratul P Srinivasan, Howard Zhou, Jonathan T Barron, Ricardo Martin-Brualla, Noah Snavely, and Thomas Funkhouser · 2021
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Learning indoor inverse rendering with 3d spatially-varying lighting
Zian Wang, Jonah Philion, Sanja Fidler, and Jan Kautz · 2021
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Outdoor inverse rendering from a single image using multiview self-supervision
Ye Yu and William A. P. Smith · 2021
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Tokens-to-token vit: Training vision transformers from scratch on imagenet
Li Yuan, Yunpeng Chen, Tao Wang, Weihao Yu, Yujun Shi, Zi-Hang Jiang, Francis EH Tay, Jiashi Feng, and Shuicheng Yan · 2021
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Lars Mescheder, Michael Oechsle, Michael Niemeyer, Sebastian Nowozin, and Andreas Geiger · 2019
Cited alongside, same era.
Multi-view relighting using a geometry-aware network
Julien Philip, Michaël Gharbi, Tinghui Zhou, Alexei A Efros, and George Drettakis · 2019
Cited alongside, same era.
Neural illumination: Lighting prediction for indoor environments
Shuran Song and Thomas Funkhouser · 2019
Cited alongside, same era.
Inverse rendering for complex indoor scenes: Shape, spatially-varying lighting and svbrdf from a single image
Zhengqin Li, Mohammad Shafiei, Ravi Ramamoorthi, Kalyan Sunkavalli, and Manmohan Chandraker · 2020
Cited alongside, same era.
Single-shot neural relighting and svbrdf estimation
Shen Sang and Manmohan Chandraker · 2020
Cited alongside, same era.
Lighthouse: Predicting lighting volumes for spatially-coherent illumination
Pratul P Srinivasan, Ben Mildenhall, Matthew Tancik, Jonathan T Barron, Richard Tucker, and Noah Snavely · 2020
Cited alongside, same era.
Mip-nerf: A multiscale representation for anti-aliasing neural radiance fields
Jonathan T Barron, Ben Mildenhall, Matthew Tancik, Peter Hedman, Ricardo Martin-Brualla, and Pratul P Srinivasan · 2021
Cited alongside, same era.
Physg: Inverse rendering with spherical gaussians for physics-based material editing and relighting
Kai Zhang, Fujun Luan, Qianqian Wang, Kavita Bala, and Noah Snavely · 2021
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Nerfactor: Neural factorization of shape and reflectance under an unknown illumination
Xiuming Zhang, Pratul P Srinivasan, Boyang Deng, Paul Debevec, William T Freeman, and Jonathan T Barron · 2021
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Mip-nerf 360: Unbounded anti-aliased neural radiance fields
Jonathan T Barron, Ben Mildenhall, Dor Verbin, Pratul P Srinivasan, and Peter Hedman · 2022
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Physically-based editing of indoor scene lighting from a single image
Zhengqin Li, Jia Shi, Sai Bi, Rui Zhu, Kalyan Sunkavalli, Miloš Hašan, Zexiang Xu, Ravi Ramamoorthi, and Manmohan Chandraker · 2022
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Phyir: Physics-based inverse rendering for panoramic indoor images
Zhen Li, Lingli Wang, Xiang Huang, Cihui Pan, and Jiaqi Yang · 2022
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Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction
Cheng Sun, Min Sun, and Hwann-Tzong Chen · 2022
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Estimating spatially-varying lighting in urban scenes with disentangled representation
Jiajun Tang, Yongjie Zhu, Haoyu Wang, Jun-Hoong Chan, Si Li, and Boxin Shi · 2022
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Ref-nerf: Structured view-dependent appearance for neural radiance fields
Dor Verbin, Peter Hedman, Ben Mildenhall, Todd Zickler, Jonathan T Barron, and Pratul P Srinivasan · 2022
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Neural light field estimation for street scenes with differentiable virtual object insertion
Zian Wang, Wenzheng Chen, David Acuna, Jan Kautz, and Sanja Fidler · 2022
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Photoscene: Photorealistic material and lighting transfer for indoor scenes
Yu-Ying Yeh, Zhengqin Li, Yannick Hold-Geoffroy, Rui Zhu, Zexiang Xu, Miloš Hašan, Kalyan Sunkavalli, and Manmohan Chandraker · 2022
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Modeling indirect illumination for inverse rendering
Yuanqing Zhang, Jiaming Sun, Xingyi He, Huan Fu, Rongfei Jia, and Xiaowei Zhou · 2022
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Learning-based inverse rendering of complex indoor scenes with differentiable monte carlo raytracing
Jingsen Zhu, Fujun Luan, Yuchi Huo, Zihao Lin, Zhihua Zhong, Dianbing Xi, Rui Wang, Hujun Bao, Jiaxiang Zheng, and Rui Tang · 2022
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Irisformer: Dense vision transformers for single-image inverse rendering in indoor scenes
Rui Zhu, Zhengqin Li, Janarbek Matai, Fatih Porikli, and Manmohan Chandraker · 2022
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