“NeRF as a Non-distant Environment Emitter in Physics-based Inverse Rendering”
Conference:
Type(s):
Title:
- NeRF as a Non-distant Environment Emitter in Physics-based Inverse Rendering
Presenter(s)/Author(s):
Abstract:
We propose utilizing NeRF as a non-distant environment lighting model in an inverse rendering pipeline. We demonstrate that our NeRF-based emitter more precisely models scene lighting than the conventional environment map, consequently enhancing the accuracy of inverse rendering.
References:
[1]
Sai Praveen Bangaru, Micha?l Gharbi, Fujun Luan, Tzu-Mao Li, Kalyan Sunkavalli, Milos Hasan, Sai Bi, Zexiang Xu, Gilbert Bernstein, and Fr?do Durand. 2022. Differentiable Rendering of Neural SDFs through Reparameterization. In SIGGRAPH Asia 2022 Conference Papers, SA 2022, Daegu, Republic of Korea, December 6-9, 2022, Soon Ki Jung, Jehee Lee, and Adam W. Bargteil (Eds.). ACM, 5:1?5:9. https://doi.org/10.1145/3550469.3555397
[2]
Sai Praveen Bangaru, Tzu-Mao Li, and Fr?do Durand. 2020. Unbiased warped-area sampling for differentiable rendering. ACM Trans. Graph. 39, 6 (2020), 245:1?245:18. https://doi.org/10.1145/3414685.3417833
[3]
Jonathan T. Barron, Ben Mildenhall, Dor Verbin, Pratul P. Srinivasan, and Peter Hedman. 2022. Mip-NeRF 360: Unbounded Anti-Aliased Neural Radiance Fields. In IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2022, New Orleans, LA, USA, June 18-24, 2022. IEEE, 5460?5469. https://doi.org/10.1109/CVPR52688.2022.00539
[4]
Jonathan T. Barron, Ben Mildenhall, Dor Verbin, Pratul P. Srinivasan, and Peter Hedman. 2023. Zip-NeRF: Anti-Aliased Grid-Based Neural Radiance Fields. In IEEE/CVF International Conference on Computer Vision, ICCV 2023, Paris, France, October 1-6, 2023. IEEE, 19640?19648. https://doi.org/10.1109/ICCV51070.2023.01804
[5]
Sai Bi, Zexiang Xu, Pratul P. Srinivasan, Ben Mildenhall, Kalyan Sunkavalli, Milos Hasan, Yannick Hold-Geoffroy, David J. Kriegman, and Ravi Ramamoorthi. 2020a. Neural Reflectance Fields for Appearance Acquisition. CoRR abs/2008.03824 (2020). arXiv:2008.03824https://arxiv.org/abs/2008.03824
[6]
Sai Bi, Zexiang Xu, Kalyan Sunkavalli, Milos Hasan, Yannick Hold-Geoffroy, David J. Kriegman, and Ravi Ramamoorthi. 2020b. Deep Reflectance Volumes: Relightable Reconstructions from Multi-view Photometric Images. In Computer Vision – ECCV 2020 – 16th European Conference, Glasgow, UK, August 23-28, 2020, Proceedings, Part III(Lecture Notes in Computer Science, Vol. 12348), Andrea Vedaldi, Horst Bischof, Thomas Brox, and Jan-Michael Frahm (Eds.). Springer, 294?311. https://doi.org/10.1007/978-3-030-58580-8_18
[7]
Mark Boss, Raphael Braun, Varun Jampani, Jonathan T. Barron, Ce Liu, and Hendrik P. A. Lensch. 2021a. NeRD: Neural Reflectance Decomposition from Image Collections. In 2021 IEEE/CVF International Conference on Computer Vision, ICCV 2021, Montreal, QC, Canada, October 10-17, 2021. IEEE, 12664?12674. https://doi.org/10.1109/ICCV48922.2021.01245
[8]
Mark Boss, Andreas Engelhardt, Abhishek Kar, Yuanzhen Li, Deqing Sun, Jonathan T. Barron, Hendrik P. A. Lensch, and Varun Jampani. 2022. SAMURAI: Shape And Material from Unconstrained Real-world Arbitrary Image collections. In Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, NeurIPS 2022, New Orleans, LA, USA, November 28 – December 9, 2022, Sanmi Koyejo, S. Mohamed, A. Agarwal, Danielle Belgrave, K. Cho, and A. Oh (Eds.). http://papers.nips.cc/paper_files/paper/2022/hash/a8f2713b5c6bdcd3d264f1aa9b9c6f03-Abstract-Conference.html
[9]
Mark Boss, Varun Jampani, Raphael Braun, Ce Liu, Jonathan T. Barron, and Hendrik P. A. Lensch. 2021b. Neural-PIL: Neural Pre-Integrated Lighting for Reflectance Decomposition. In Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, NeurIPS 2021, December 6-14, 2021, virtual, Marc?Aurelio Ranzato, Alina Beygelzimer, Yann N. Dauphin, Percy Liang, and Jennifer Wortman Vaughan (Eds.). 10691?10704. https://proceedings.neurips.cc/paper/2021/hash/58ae749f25eded36f486bc85feb3f0ab-Abstract.html
[10]
Brent Burley. 2012. Physically Based Shading at Disney. In SIGGRAPH 2012 Course Notes. https://www.disneyanimation.com/publications/physically-based-shading-at-disney/
[11]
Wesley Chang, Venkataram Sivaram, Derek Nowrouzezahrai, Toshiya Hachisuka, Ravi Ramamoorthi, and Tzu-Mao Li. 2023. Parameter-space ReSTIR for Differentiable and Inverse Rendering. In ACM SIGGRAPH 2023 Conference Proceedings, SIGGRAPH 2023, Los Angeles, CA, USA, August 6-10, 2023, Erik Brunvand, Alla Sheffer, and Michael Wimmer (Eds.). ACM, 18:1?18:10. https://doi.org/10.1145/3588432.3591512
[12]
Zhaoxi Chen and Ziwei Liu. 2022. Relighting4D: Neural Relightable Human from Videos. In Computer Vision – ECCV 2022 – 17th European Conference, Tel Aviv, Israel, October 23-27, 2022, Proceedings, Part XIV(Lecture Notes in Computer Science, Vol. 13674), Shai Avidan, Gabriel J. Brostow, Moustapha Ciss?, Giovanni Maria Farinella, and Tal Hassner (Eds.). Springer, 606?623. https://doi.org/10.1007/978-3-031-19781-9_35
[13]
Jorge Condor and Adri?n Jarabo. 2022. A Learned Radiance-Field Representation for Complex Luminaires. In 33rd Eurographics Symposium on Rendering, EGSR 2022 – Symposium Track, Prague, Czech Republic, 4-6 July 2022, Abhijeet Ghosh and Li-Yi Wei (Eds.). Eurographics Association, 49?58. https://doi.org/10.2312/SR.20221155
[14]
Brian Curless and Marc Levoy. 1996. A Volumetric Method for Building Complex Models from Range Images. In Proceedings of the 23rd Annual Conference on Computer Graphics and Interactive Techniques, SIGGRAPH 1996, New Orleans, LA, USA, August 4-9, 1996, John Fujii (Ed.). ACM, 303?312. https://doi.org/10.1145/237170.237269
[15]
Paul E. Debevec and Jitendra Malik. 1997. Recovering high dynamic range radiance maps from photographs. In Proceedings of the 24th Annual Conference on Computer Graphics and Interactive Techniques, SIGGRAPH 1997, Los Angeles, CA, USA, August 3-8, 1997, G. Scott Owen, Turner Whitted, and Barbara Mones-Hattal (Eds.). ACM, 369?378. https://doi.org/10.1145/258734.258884
[16]
Wenhang Ge, Tao Hu, Haoyu Zhao, Shu Liu, and Ying-Cong Chen. 2023. Ref-NeuS: Ambiguity-Reduced Neural Implicit Surface Learning for Multi-View Reconstruction with Reflection. In IEEE/CVF International Conference on Computer Vision, ICCV 2023, Paris, France, October 1-6, 2023. IEEE, 4228?4237. https://doi.org/10.1109/ICCV51070.2023.00392
[17]
Param Hanji and Rafal K. Mantiuk. 2023. Robust Estimation of Exposure Ratios in Multi-Exposure Image Stacks. IEEE Trans. Computational Imaging 9 (2023), 721?731. https://doi.org/10.1109/TCI.2023.3301338
[18]
Param Hanji, Fangcheng Zhong, and Rafal K. Mantiuk. 2020. Noise-Aware Merging of High Dynamic Range Image Stacks Without Camera Calibration. In Computer Vision – ECCV 2020 Workshops – Glasgow, UK, August 23-28, 2020, Proceedings, Part III(Lecture Notes in Computer Science, Vol. 12537), Adrien Bartoli and Andrea Fusiello (Eds.). Springer, 376?391. https://doi.org/10.1007/978-3-030-67070-2_23
[19]
Jon Hasselgren, Nikolai Hofmann, and Jacob Munkberg. 2022. Shape, Light, and Material Decomposition from Images using Monte Carlo Rendering and Denoising. In Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, NeurIPS 2022, New Orleans, LA, USA, November 28 – December 9, 2022, Sanmi Koyejo, S. Mohamed, A. Agarwal, Danielle Belgrave, K. Cho, and A. Oh (Eds.). http://papers.nips.cc/paper_files/paper/2022/hash/8fcb27984bf16ca03cad643244ec470d-Abstract-Conference.html
[20]
Wenzel Jakob. 2012. Numerically stable sampling of the von Mises-Fisher distribution on S?2 (and other tricks). Interactive Geometry Lab, ETH Z?rich, Tech. Rep (2012), 6.
[21]
Wenzel Jakob, S?bastien Speierer, Nicolas Roussel, Merlin Nimier-David, Delio Vicini, Tizian Zeltner, Baptiste Nicolet, Miguel Crespo, Vincent Leroy, and Ziyi Zhang. 2022b. Mitsuba 3 renderer. https://mitsuba-renderer.org.
[22]
Wenzel Jakob, S?bastien Speierer, Nicolas Roussel, and Delio Vicini. 2022a. DR.JIT: a just-in-time compiler for differentiable rendering. ACM Trans. Graph. 41, 4 (2022), 124:1?124:19. https://doi.org/10.1145/3528223.3530099
[23]
Haian Jin, Isabella Liu, Peijia Xu, Xiaoshuai Zhang, Songfang Han, Sai Bi, Xiaowei Zhou, Zexiang Xu, and Hao Su. 2023. TensoIR: Tensorial Inverse Rendering. In IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2023, Vancouver, BC, Canada, June 17-24, 2023. IEEE, 165?174. https://doi.org/10.1109/CVPR52729.2023.00024
[24]
Ondrej Karl?k, Martin Sik, Petr V?voda, Tom?s Skrivan, and Jaroslav Kriv?nek. 2019. MIS compensation: optimizing sampling techniques in multiple importance sampling. ACM Trans. Graph. 38, 6 (2019), 151:1?151:12. https://doi.org/10.1145/3355089.3356565
[25]
Diederik P. Kingma and Jimmy Ba. 2015. Adam: A Method for Stochastic Optimization. In 3rd International Conference on Learning Representations, ICLR 2015, San Diego, CA, USA, May 7-9, 2015, Conference Track Proceedings, Yoshua Bengio and Yann LeCun (Eds.). http://arxiv.org/abs/1412.6980
[26]
Tzu-Mao Li, Miika Aittala, Fr?do Durand, and Jaakko Lehtinen. 2018. Differentiable Monte Carlo ray tracing through edge sampling. ACM Trans. Graph. 37, 6 (2018), 222. https://doi.org/10.1145/3272127.3275109
[27]
Chen-Hsuan Lin, Wei-Chiu Ma, Antonio Torralba, and Simon Lucey. 2021. BARF: Bundle-Adjusting Neural Radiance Fields. In 2021 IEEE/CVF International Conference on Computer Vision, ICCV 2021, Montreal, QC, Canada, October 10-17, 2021. IEEE, 5721?5731. https://doi.org/10.1109/ICCV48922.2021.00569
[28]
Jingwang Ling, Zhibo Wang, and Feng Xu. 2023. ShadowNeuS: Neural SDF Reconstruction by Shadow Ray Supervision. In IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2023, Vancouver, BC, Canada, June 17-24, 2023. IEEE, 175?185. https://doi.org/10.1109/CVPR52729.2023.00025
[29]
Ben Mildenhall, Peter Hedman, Ricardo Martin-Brualla, Pratul P. Srinivasan, and Jonathan T. Barron. 2022. NeRF in the Dark: High Dynamic Range View Synthesis from Noisy Raw Images. In IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2022, New Orleans, LA, USA, June 18-24, 2022. IEEE, 16169?16178. https://doi.org/10.1109/CVPR52688.2022.01571
[30]
Ben Mildenhall, Pratul P. Srinivasan, Matthew Tancik, Jonathan T. Barron, Ravi Ramamoorthi, and Ren Ng. 2020. NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis. In Computer Vision – ECCV 2020 – 16th European Conference, Glasgow, UK, August 23-28, 2020, Proceedings, Part I(Lecture Notes in Computer Science, Vol. 12346), Andrea Vedaldi, Horst Bischof, Thomas Brox, and Jan-Michael Frahm (Eds.). Springer, 405?421. https://doi.org/10.1007/978-3-030-58452-8_24
[31]
Thomas M?ller, Alex Evans, Christoph Schied, and Alexander Keller. 2022. Instant neural graphics primitives with a multiresolution hash encoding. ACM Trans. Graph. 41, 4 (2022), 102:1?102:15. https://doi.org/10.1145/3528223.3530127
[32]
Thomas M?ller, Markus H. Gross, and Jan Nov?k. 2017. Practical Path Guiding for Efficient Light-Transport Simulation. Comput. Graph. Forum 36, 4 (2017), 91?100. https://doi.org/10.1111/CGF.13227
[33]
Baptiste Nicolet, Fabrice Rousselle, Jan Nov?k, Alexander Keller, Wenzel Jakob, and Thomas M?ller. 2023. Recursive Control Variates for Inverse Rendering. ACM Trans. Graph. 42, 4 (2023), 62:1?62:13. https://doi.org/10.1145/3592139
[34]
Merlin Nimier-David, S?bastien Speierer, Beno?t Ruiz, and Wenzel Jakob. 2020. Radiative backpropagation: an adjoint method for lightning-fast differentiable rendering. ACM Trans. Graph. 39, 4 (2020), 146. https://doi.org/10.1145/3386569.3392406
[35]
Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, Alban Desmaison, Andreas K?pf, Edward Z. Yang, Zachary DeVito, Martin Raison, Alykhan Tejani, Sasank Chilamkurthy, Benoit Steiner, Lu Fang, Junjie Bai, and Soumith Chintala. 2019. PyTorch: An Imperative Style, High-Performance Deep Learning Library. In Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, NeurIPS 2019, December 8-14, 2019, Vancouver, BC, Canada, Hanna M. Wallach, Hugo Larochelle, Alina Beygelzimer, Florence d?Alch?-Buc, Emily B. Fox, and Roman Garnett (Eds.). 8024?8035. https://proceedings.neurips.cc/paper/2019/hash/bdbca288fee7f92f2bfa9f7012727740-Abstract.html
[36]
Julien Philip and Valentin Deschaintre. 2023. Radiance Field Gradient Scaling for Unbiased Near-Camera Training. CoRR abs/2305.02756 (2023). https://doi.org/10.48550/ARXIV.2305.02756 arXiv:2305.02756
[37]
Yi-Ling Qiao, Alexander Gao, Yiran Xu, Yue Feng, Jia-Bin Huang, and Ming C. Lin. 2023. Dynamic Mesh-Aware Radiance Fields. In IEEE/CVF International Conference on Computer Vision, ICCV 2023, Paris, France, October 1-6, 2023. IEEE, 385?396. https://doi.org/10.1109/ICCV51070.2023.00042
[38]
Radu Alexandru Rosu and Sven Behnke. 2023. PermutoSDF: Fast Multi-View Reconstruction with Implicit Surfaces Using Permutohedral Lattices. In IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2023, Vancouver, BC, Canada, June 17-24, 2023. IEEE, 8466?8475. https://doi.org/10.1109/CVPR52729.2023.00818
[39]
Viktor Rudnev, Mohamed Elgharib, William A. P. Smith, Lingjie Liu, Vladislav Golyanik, and Christian Theobalt. 2021. Neural Radiance Fields for Outdoor Scene Relighting. CoRR abs/2112.05140 (2021). arXiv:2112.05140https://arxiv.org/abs/2112.05140
[40]
Pratul P. Srinivasan, Boyang Deng, Xiuming Zhang, Matthew Tancik, Ben Mildenhall, and Jonathan T. Barron. 2021. NeRV: Neural Reflectance and Visibility Fields for Relighting and View Synthesis. In IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2021, virtual, June 19-25, 2021. Computer Vision Foundation / IEEE, 7495?7504. https://doi.org/10.1109/CVPR46437.2021.00741
[41]
Cheng Sun, Guangyan Cai, Zhengqin Li, Kai Yan, Cheng Zhang, Carl Marshall, Jia-Bin Huang, Shuang Zhao, and Zhao Dong. 2023. Neural-PBIR Reconstruction of Shape, Material, and Illumination. In IEEE/CVF International Conference on Computer Vision, ICCV 2023, Paris, France, October 1-6, 2023. IEEE, 18000?18010. https://doi.org/10.1109/ICCV51070.2023.01654
[42]
Matthew Tancik, Ethan Weber, Evonne Ng, Ruilong Li, Brent Yi, Terrance Wang, Alexander Kristoffersen, Jake Austin, Kamyar Salahi, Abhik Ahuja, David McAllister, Justin Kerr, and Angjoo Kanazawa. 2023. Nerfstudio: A Modular Framework for Neural Radiance Field Development. In ACM SIGGRAPH 2023 Conference Proceedings, SIGGRAPH 2023, Los Angeles, CA, USA, August 6-10, 2023, Erik Brunvand, Alla Sheffer, and Michael Wimmer (Eds.). ACM, 72:1?72:12. https://doi.org/10.1145/3588432.3591516
[43]
Eric Veach. 1997. Robust Monte Carlo methods for light transport simulation. Ph. D. Dissertation. Stanford University, USA. https://searchworks.stanford.edu/view/3911108
[44]
Delio Vicini, S?bastien Speierer, and Wenzel Jakob. 2021. Path replay backpropagation: differentiating light paths using constant memory and linear time. ACM Trans. Graph. 40, 4 (2021), 108:1?108:14. https://doi.org/10.1145/3450626.3459804
[45]
Delio Vicini, S?bastien Speierer, and Wenzel Jakob. 2022. Differentiable signed distance function rendering. ACM Trans. Graph. 41, 4 (2022), 125:1?125:18. https://doi.org/10.1145/3528223.3530139
[46]
Peng Wang, Lingjie Liu, Yuan Liu, Christian Theobalt, Taku Komura, and Wenping Wang. 2021. NeuS: Learning Neural Implicit Surfaces by Volume Rendering for Multi-view Reconstruction. In Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, NeurIPS 2021, December 6-14, 2021, virtual, Marc?Aurelio Ranzato, Alina Beygelzimer, Yann N. Dauphin, Percy Liang, and Jennifer Wortman Vaughan (Eds.). 27171?27183. https://proceedings.neurips.cc/paper/2021/hash/e41e164f7485ec4a28741a2d0ea41c74-Abstract.html
[47]
Yu-Chen Wang, Chris Wyman, Lifan Wu, and Shuang Zhao. 2023b. Amortizing Samples in Physics-Based Inverse Rendering Using ReSTIR. ACM Trans. Graph. 42, 6 (2023), 214:1?214:17. https://doi.org/10.1145/3618331
[48]
Zian Wang, Tianchang Shen, Merlin Nimier-David, Nicholas Sharp, Jun Gao, Alexander Keller, Sanja Fidler, Thomas M?ller, and Zan Gojcic. 2023a. Adaptive Shells for Efficient Neural Radiance Field Rendering. ACM Trans. Graph. 42, 6 (2023), 260:1?260:15. https://doi.org/10.1145/3618390
[49]
Haoqian Wu, Zhipeng Hu, Lincheng Li, Yongqiang Zhang, Changjie Fan, and Xin Yu. 2023. NeFII: Inverse Rendering for Reflectance Decomposition with Near-Field Indirect Illumination. In IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2023, Vancouver, BC, Canada, June 17-24, 2023. IEEE, 4295?4304. https://doi.org/10.1109/CVPR52729.2023.00418
[50]
Linning Xu, Vasu Agrawal, William Laney, Tony Garcia, Aayush Bansal, Changil Kim, Samuel Rota Bul?, Lorenzo Porzi, Peter Kontschieder, Aljaz Bozic, Dahua Lin, Michael Zollh?fer, and Christian Richardt. 2023a. VR-NeRF: High-Fidelity Virtualized Walkable Spaces. In SIGGRAPH Asia 2023 Conference Papers, SA 2023, Sydney, NSW, Australia, December 12-15, 2023, June Kim, Ming C. Lin, and Bernd Bickel (Eds.). ACM, 43:1?43:12. https://doi.org/10.1145/3610548.3618139
[51]
Peiyu Xu, Sai Praveen Bangaru, Tzu-Mao Li, and Shuang Zhao. 2023b. Warped-Area Reparameterization of Differential Path Integrals. ACM Trans. Graph. 42, 6 (2023), 213:1?213:18. https://doi.org/10.1145/3618330
[52]
Wenqi Yang, Guanying Chen, Chaofeng Chen, Zhenfang Chen, and Kwan-Yee K. Wong. 2022a. PS-NeRF: Neural Inverse Rendering for Multi-view Photometric Stereo. In Computer Vision – ECCV 2022 – 17th European Conference, Tel Aviv, Israel, October 23-27, 2022, Proceedings, Part I(Lecture Notes in Computer Science, Vol. 13661), Shai Avidan, Gabriel J. Brostow, Moustapha Ciss?, Giovanni Maria Farinella, and Tal Hassner (Eds.). Springer, 266?284. https://doi.org/10.1007/978-3-031-19769-7_16
[53]
Wenqi Yang, Guanying Chen, Chaofeng Chen, Zhenfang Chen, and Kwan-Yee K. Wong. 2022b. S3-NeRF: Neural Reflectance Field from Shading and Shadow under a Single Viewpoint. In Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, NeurIPS 2022, New Orleans, LA, USA, November 28 – December 9, 2022, Sanmi Koyejo, S. Mohamed, A. Agarwal, Danielle Belgrave, K. Cho, and A. Oh (Eds.). http://papers.nips.cc/paper_files/paper/2022/hash/0a630402ee92620dc2de3b704181de9b-Abstract-Conference.html
[54]
Lior Yariv, Peter Hedman, Christian Reiser, Dor Verbin, Pratul P. Srinivasan, Richard Szeliski, Jonathan T. Barron, and Ben Mildenhall. 2023. BakedSDF: Meshing Neural SDFs for Real-Time View Synthesis. In ACM SIGGRAPH 2023 Conference Proceedings, SIGGRAPH 2023, Los Angeles, CA, USA, August 6-10, 2023, Erik Brunvand, Alla Sheffer, and Michael Wimmer (Eds.). ACM, 46:1?46:9. https://doi.org/10.1145/3588432.3591536
[55]
Tizian Zeltner, S?bastien Speierer, Iliyan Georgiev, and Wenzel Jakob. 2021. Monte Carlo estimators for differential light transport. ACM Trans. Graph. 40, 4 (2021), 78:1?78:16. https://doi.org/10.1145/3450626.3459807
[56]
Cheng Zhang, Bailey Miller, Kai Yan, Ioannis Gkioulekas, and Shuang Zhao. 2020. Path-space differentiable rendering. ACM Trans. Graph. 39, 4 (2020), 143. https://doi.org/10.1145/3386569.3392383
[57]
Cheng Zhang, Lifan Wu, Changxi Zheng, Ioannis Gkioulekas, Ravi Ramamoorthi, and Shuang Zhao. 2019. A differential theory of radiative transfer. ACM Trans. Graph. 38, 6 (2019), 227:1?227:16. https://doi.org/10.1145/3355089.3356522
[58]
Kai Zhang, Fujun Luan, Zhengqi Li, and Noah Snavely. 2022a. IRON: Inverse Rendering by Optimizing Neural SDFs and Materials from Photometric Images. In IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2022, New Orleans, LA, USA, June 18-24, 2022. IEEE, 5555?5564. https://doi.org/10.1109/CVPR52688.2022.00548
[59]
Kai Zhang, Fujun Luan, Qianqian Wang, Kavita Bala, and Noah Snavely. 2021. PhySG: Inverse Rendering With Spherical Gaussians for Physics-Based Material Editing and Relighting. In IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2021, virtual, June 19-25, 2021. Computer Vision Foundation / IEEE, 5453?5462. https://doi.org/10.1109/CVPR46437.2021.00541
[60]
Yuanqing Zhang, Jiaming Sun, Xingyi He, Huan Fu, Rongfei Jia, and Xiaowei Zhou. 2022b. Modeling Indirect Illumination for Inverse Rendering. In IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2022, New Orleans, LA, USA, June 18-24, 2022. IEEE, 18622?18631. https://doi.org/10.1109/CVPR52688.2022.01809
[61]
Junqiu Zhu, Yaoyi Bai, Zilin Xu, Steve Bako, Edgar Vel?zquez-Armend?riz, Lu Wang, Pradeep Sen, Milos Hasan, and Ling-Qi Yan. 2021. Neural complex luminaires: representation and rendering. ACM Trans. Graph. 40, 4 (2021), 57:1?57:12. https://doi.org/10.1145/3450626.3459798
