[22] Jooyoung Choi, Sungwon Kim, Yonghyun Jeong, Youngjune Gwon, and Sungroh Yoon. Ilvr: Conditioning method for denoising diffusion probabilistic models. Proc. ICCV, 2021. 5
[23] Bahjat Kawar, Michael Elad, Stefano Ermon, and Jiaming Song. Denoising diffusion restoration models. In Proc. NeurIPS, 2022. 5
[24] Jiaming Song, Arash Vahdat, Morteza Mardani, and Jan Kautz. Pseudoinverse-guided diffusion models for inverse problems. In Proc. ICLR, 2023. 5
[25] Zahra Kadkhodaie and Eero Simoncelli. Stochastic solutions for linear inverse problems using the prior implicit in a denoiser. Advances in Neural Information Processing Systems, 34:13242-13254, 2021. 5
[26] Yang Song, Jascha Sohl-Dickstein, Diederik P Kingma, Abhishek Kumar, Stefano Ermon, and Ben Poole. Score-based generative modeling through stochastic differential equations. In Proc. ICLR, 2021. 5
[27] Yang Song, Liyue Shen, Lei Xing, and Stefano Ermon. Solving inverse problems in medical imaging with score-based generative models. Proc. ICLR, 2022. 5
[28] Johnathan M Bardsley. Mcmc-based image reconstruction with uncertainty quantification. SIAM Journal on Scientific Computing, 34(3):A1316-A1332, 2012. 5
[29] Singanallur Venkatakrishnan, Charles A. Bouman, and Brendt Wohlberg. Plug-and-play priors for model based reconstruction. 2013 IEEE Global Conference on Signal and Information Processing, pages 945-948, 2013. 5
[30] Yaniv Romano, Michael Elad, and Peyman Milanfar. The little engine that could: Regularization by denoising (red). SIAM Journal on Imaging Sciences, 10(4):1804-1844, 2017. 5
[31] Vincent Sitzmann, Michael Zollhöfer, and Gordon Wetzstein. Scene representation networks: Continuous 3d-structure-aware neural scene representations. Proc. NeurIPS, 2019. 6
[32] Michael Niemeyer, Lars Mescheder, Michael Oechsle, and Andreas Geiger. Differentiable volumetric rendering: Learning implicit 3d representations without 3d supervision. In Proc. CVPR, 2020. 6
[33] Philipp Henzler, Jeremy Reizenstein, Patrick Labatut, Roman Shapovalov, Tobias Ritschel, Andrea Vedaldi, and David Novotny. Unsupervised learning of 3d object categories from videos in the wild. In Proc. CVPR, 2021. 6
[34] Prafull Sharma, Ayush Tewari, Yilun Du, Sergey Zakharov, Rares Andrei Ambrus, Adrien Gaidon, William T Freeman, Fredo Durand, Joshua B Tenenbaum, and Vincent Sitzmann. Neural groundplans: Persistent neural scene representations from a single image. In Proc. ICLR. 6
[35] Anpei Chen, Zexiang Xu, Fuqiang Zhao, Xiaoshuai Zhang, Fanbo Xiang, Jingyi Yu, and Hao Su. Mvsnerf: Fast generalizable radiance field reconstruction from multi-view stereo. In Proc. ICCV, 2021. 6
[36] Yilun Du, Cameron Smith, Ayush Tewari, and Vincent Sitzmann. Learning to render novel views from wide-baseline stereo pairs. In Proc. CVPR, 2023. 6
[37] Alex Trevithick and Bo Yang. Grf: Learning a general radiance field for 3d representation and rendering. In Proc. ICCV, 2021. 6
[38] Mohammed Suhail, Carlos Esteves, Leonid Sigal, and Ameesh Makadia. Generalizable patch-based neural rendering. In Proc. ECCV, 2022. 6
[39] Julian Chibane, Aayush Bansal, Verica Lazova, and Gerard Pons-Moll. Stereo radiance fields (srf): Learning view synthesis for sparse views of novel scenes. In Proc. CVPR, 2021. 6
[40] Qianqian Wang, Zhicheng Wang, Kyle Genova, Pratul P Srinivasan, Howard Zhou, Jonathan T Barron, Ricardo Martin-Brualla, Noah Snavelly, and Thomas Funkhouser. Ibrnet: Learning multi-view image-based rendering. In Proc. CVPR, 2021. 6
[41] Shamit Lal, Mihir Prabhudesai, Ishita Mediratta, Adam W Harley, and Katerina Fragkiadaki. Coconets: Continuous contrastive 3d scene representations. In Proc. CVPR, 2021. 6
[42] Daniel Watson, William Chan, Ricardo Martin-Brualla, Jonathan Ho, Andrea Tagliasacchi, and Mohammad Norouzi. Novel view synthesis with diffusion models. Proc. ICLR, 2023. 6
[43] SM Ali Eslami, Danilo Jimenez Rezende, Frederic Besse, Fabio Viola, Ari S Morcos, Marta Garnelo, Avraham Ruderman, Andrei A Rusu, Ivo Danihelka, Karol Gregor, et al. Neural scene representation and rendering. Science, 360(6394):1204-1210, 2018. 6