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Inverse rendering seeks to recover 3D geometry, surface material, and lighting from captured images, enabling advanced applications such as novel-view synthesis, relighting, and virtual object insertion.
A reflectance model for computer graphics
Robert L Cook and Kenneth E. Torrance · 1982
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The rendering equation
James T Kajiya · 1986
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Mathematical models and Monte Carlo algorithms for physically based rendering
Eric Lafortune · 1996
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Recovering high dynamic range radiance maps from photographs
Paul E. Debevec and Jitendra Malik · 1997
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What is the space of camera response functions?
Michael D Grossberg and Shree K Nayar · 2003
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Modeling the space of camera response functions
Michael D. Grossberg and Shree K. Nayar · 2004
Earlier work this paper cites.
Shape and spatially-varying BRDFs from photometric stereo
Dan B Goldman, Brian Curless, Aaron Hertzmann, and Steven M Seitz · 2009
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High Dynamic Range Imaging – Acquisition, Display and Image-Based Lighting
Erik Reinhard, Greg Ward, Sumanta Pattanaik, Paul Debevec, Wolfgang Heidrich, and Karol Myszkowski · 2010
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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
Earlier work this paper cites.
Modeling surface appearance from a single photograph using self-augmented convolutional neural networks
Xiao Li, Yue Dong, Pieter Peers, and Xin Tong · 2017
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Learning high dynamic range from outdoor panoramas
Jinsong Zhang and Jean-François Lalonde · 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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Materials for masses: SVBRDF acquisition with a single mobile phone image
Zhengqin Li, Kalyan Sunkavalli, and Manmohan Chandraker · 2018
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ExpandNet: A deep convolutional neural network for high dynamic range expansion from low dynamic range content
Demetris Marnerides, Thomas Bashford-Rogers, Jonathan Hatchett, and Kurt Debattista · 2018
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Image correction via deep reciprocating HDR transformation
Xin Yang, Ke Xu, Yibing Song, Qiang Zhang, Xiaopeng Wei, and Rynson WH Lau · 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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Neural reflectance fields for appearance acquisition
Sai Bi, Zexiang Xu, Pratul Srinivasan, Ben Mildenhall, Kalyan Sunkavalli, Miloš Hašan, Yannick Hold-Geoffroy, David Kriegman, and Ravi Ramamoorthi · 2020
Earlier work this paper cites.
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-image HDR reconstruction by learning to reverse the camera pipeline
Yu-Lun Liu, Wei-Sheng Lai, Yu-Sheng Chen, Yi-Lung Kao, Ming-Hsuan Yang, Yung-Yu Chuang, and Jia-Bin Huang · 2020
Cited alongside, same era.
NeRF: Representing scenes as neural radiance fields for view synthesis
Ben Mildenhall, Pratul P. Srinivasan, Matthew Tancik, Jonathan T. Barron, Ravi Ramamoorthi, and Ren Ng · 2020
Cited alongside, same era.
The design and evolution of the UberBake light baking system
Dario Seyb, Peter-Pike Sloan, Ari Silvennoinen, Michał Iwanicki, and Wojciech Jarosz · 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.
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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NeRF in the dark: High dynamic range view synthesis from noisy raw images
Ben Mildenhall, Peter Hedman, Ricardo Martin-Brualla, Pratul Srinivasan, and Jonathan T. Barron · 2022
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Instant neural graphics primitives with a multiresolution hash encoding
Thomas Müller, Alex Evans, Christoph Schied, and Alexander Keller · 2022
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Extracting triangular 3D models, materials, and lighting from images
Jacob Munkberg, Jon Hasselgren, Tianchang Shen, Jun Gao, Wenzheng Chen, Alex Evans, Thomas Müller, and Sanja Fidler · 2022
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NeILF: Neural incident light field for physically-based material estimation
Yao Yao, Jingyang Zhang, Jingbo Liu, Yihang Qu, Tian Fang, David McKinnon, Yanghai Tsin, and Long Quan · 2022
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Omnidata: A scalable pipeline for making multi-task mid-level vision datasets from 3D scans
Ainaz Eftekhar, Alexander Sax, Jitendra Malik, and Amir Zamir · 2021
Cited alongside, same era.
OpenRooms: An open framework for photorealistic indoor scene datasets
Zhengqin Li, Ting-Wei Yu, Shen Sang, Sarah Wang, Meng Song, Yuhan Liu, Yu-Ying Yeh, Rui Zhu, Nitesh Gundavarapu, Jia Shi, et al · 2021
Cited alongside, same era.
Material and lighting reconstruction for complex indoor scenes with texture-space differentiable rendering
Merlin Nimier-David, Zhao Dong, Wenzel Jakob, and Anton Kaplanyan · 2021
Cited alongside, same era.
Free-viewpoint indoor neural relighting from multi-view stereo
Julien Philip, Sébastien Morgenthaler, Michaël Gharbi, and George Drettakis · 2021
Cited alongside, same era.
Hypersim: A photorealistic synthetic dataset for holistic indoor scene understanding
Mike Roberts, Jason Ramapuram, Anurag Ranjan, Atulit Kumar, Miguel Angel Bautista, Nathan Paczan, Russ Webb, and Joshua M. Susskind · 2021
Cited alongside, same era.
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
Cited alongside, same era.
Learning indoor inverse rendering with 3D spatially-varying lighting
Zian Wang, Jonah Philion, Sanja Fidler, and Jan Kautz · 2021
Cited alongside, same era.
MonoSDF: Exploring monocular geometric cues for neural implicit surface reconstruction
Zehao Yu, Songyou Peng, Michael Niemeyer, Torsten Sattler, and Andreas Geiger · 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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TensoIR: Tensorial inverse rendering
Haian Jin, Isabella Liu, Peijia Xu, Xiaoshuai Zhang, Songfang Han, Sai Bi, Xiaowei Zhou, Zexiang Xu, and Hao Su · 2023
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Neural-pbir reconstruction of shape, material, and illumination
Cheng Sun, Guangyan Cai, Zhengqin Li, Kai Yan, Cheng Zhang, Carl Marshall, Jia-Bin Huang, Shuang Zhao, and Zhao Dong · 2023
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Neural fields meet explicit geometric representations for inverse rendering of urban scenes
Zian Wang, Tianchang Shen, Jun Gao, Shengyu Huang, Jacob Munkberg, Jon Hasselgren, Zan Gojcic, Wenzheng Chen, and Sanja Fidler · 2023
Later among the works it cites.
Bakedsdf: Meshing neural sdfs for real-time view synthesis
Lior Yariv, Peter Hedman, Christian Reiser, Dor Verbin, Pratul P Srinivasan, Richard Szeliski, Jonathan T Barron, and Ben Mildenhall · 2023
Later among the works it cites.
ScanNet++: A high-fidelity dataset of 3D indoor scenes
Chandan Yeshwanth, Yueh-Cheng Liu, Matthias Nießner, and Angela Dai · 2023
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MILO: Multi-bounce inverse rendering for indoor scene with light-emitting objects
Bohan Yu, Siqi Yang, Xuanning Cui, Siyan Dong, Baoquan Chen, and Boxin Shi · 2023
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NeILF++: Inter-reflectable light fields for geometry and material estimation
Jingyang Zhang, Yao Yao, Shiwei Li, Jingbo Liu, Tian Fang, David McKinnon, Yanghai Tsin, and Long Quan · 2023
Later among the works it cites.
I 2 -SDF: Intrinsic indoor scene reconstruction and editing via raytracing in neural SDFs
Jingsen Zhu, Yuchi Huo, Qi Ye, Fujun Luan, Jifan Li, Dianbing Xi, Lisha Wang, Rui Tang, Wei Hua, Hujun Bao, and Rui Wang · 2023
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RGB ↔ \leftrightarrow X: Image decomposition and synthesis using material- and lighting-aware diffusion models
Zheng Zeng, Valentin Deschaintre, Iliyan Georgiev, Yannick Hold-Geoffroy, Yiwei Hu, Fujun Luan, Ling-Qi Yan, and Miloš Hašan · 2024
Closest in time.
UrbanIR: Large-scale urban scene inverse rendering from a single video
Zhi-Hao Lin, Bohan Liu, Yi-Ting Chen, David Forsyth, Jia-Bin Huang, Anand Bhattad, and Shenlong Wang · 2025
Closest in time.