{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,6]],"date-time":"2026-05-06T15:11:31Z","timestamp":1778080291801,"version":"3.51.4"},"publisher-location":"New York, NY, USA","reference-count":50,"publisher":"ACM","license":[{"start":{"date-parts":[[2023,6,17]],"date-time":"2023-06-17T00:00:00Z","timestamp":1686960000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000001","name":"NSF (National Science Foundation)","doi-asserted-by":"publisher","award":["2211815"],"award-info":[{"award-number":["2211815"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000028","name":"Semiconductor Research Corporation","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000028","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2023,6,17]]},"DOI":"10.1145\/3579371.3589109","type":"proceedings-article","created":{"date-parts":[[2023,6,16]],"date-time":"2023-06-16T20:25:28Z","timestamp":1686947128000},"page":"1-12","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":33,"title":["Gen-NeRF: Efficient and Generalizable Neural Radiance Fields via Algorithm-Hardware Co-Design"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7483-2921","authenticated-orcid":false,"given":"Yonggan","family":"Fu","sequence":"first","affiliation":[{"name":"School of Computer Science, Georgia Institute of Technology, Atlanta, Georgia, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0755-8843","authenticated-orcid":false,"given":"Zhifan","family":"Ye","sequence":"additional","affiliation":[{"name":"School of Computer Science, Georgia Institute of Technology, Atlanta, Georgia, USA"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-9208-6677","authenticated-orcid":false,"given":"Jiayi","family":"Yuan","sequence":"additional","affiliation":[{"name":"Rice University, Houston, Texas, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6227-6905","authenticated-orcid":false,"given":"Shunyao","family":"Zhang","sequence":"additional","affiliation":[{"name":"Rice University, Houston, Texas, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9105-9299","authenticated-orcid":false,"given":"Sixu","family":"Li","sequence":"additional","affiliation":[{"name":"School of Computer Science, Georgia Institute of Technology, Atlanta, Texas, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2873-2153","authenticated-orcid":false,"given":"Haoran","family":"You","sequence":"additional","affiliation":[{"name":"School of Computer Science, Georgia Institute of Technology, Atlanta, Georgia, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5946-203X","authenticated-orcid":false,"given":"Yingyan","family":"Lin","sequence":"additional","affiliation":[{"name":"School of Computer Science, Georgia Institute of Technology, Atlanta, Georgia, USA"}]}],"member":"320","published-online":{"date-parts":[[2023,6,17]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"Neural Reflectance Fields for Appearance Acquisition. arXiv cs.CV arXiv:2008.03824","author":"Bi Sai","year":"2020","unstructured":"Sai Bi , Zexiang Xu , Pratul P. Srinivasan , Ben Mildenhall , Kalyan Sunkavalli , Milo\u0161 Ha\u0161an , Yannick Hold-Geoffroy , David Kriegman , and Ravi Ramamoorthi . 2020. Neural Reflectance Fields for Appearance Acquisition. arXiv cs.CV arXiv:2008.03824 ( 2020 ). Sai Bi, Zexiang Xu, Pratul P. Srinivasan, Ben Mildenhall, Kalyan Sunkavalli, Milo\u0161 Ha\u0161an, Yannick Hold-Geoffroy, David Kriegman, and Ravi Ramamoorthi. 2020. Neural Reflectance Fields for Appearance Acquisition. arXiv cs.CV arXiv:2008.03824 (2020)."},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00779-016-0953-5"},{"key":"e_1_3_2_1_3_1","volume-title":"pi-GAN: Periodic Implicit Generative Adversarial Networks for 3D-Aware Image Synthesis. CVPR","author":"Chan Eric R.","year":"2021","unstructured":"Eric R. Chan , Marco Monteiro , Petr Kellnhofer , Jiajun Wu , and Gordon Wetzstein . 2021. pi-GAN: Periodic Implicit Generative Adversarial Networks for 3D-Aware Image Synthesis. CVPR ( 2021 ). Eric R. Chan, Marco Monteiro, Petr Kellnhofer, Jiajun Wu, and Gordon Wetzstein. 2021. pi-GAN: Periodic Implicit Generative Adversarial Networks for 3D-Aware Image Synthesis. CVPR (2021)."},{"key":"e_1_3_2_1_4_1","volume-title":"TensoRF: Tensorial Radiance Fields. arXiv preprint arXiv:2203.09517","author":"Chen Anpei","year":"2022","unstructured":"Anpei Chen , Zexiang Xu , Andreas Geiger , Jingyi Yu , and Hao Su. 2022. TensoRF: Tensorial Radiance Fields. arXiv preprint arXiv:2203.09517 ( 2022 ). Anpei Chen, Zexiang Xu, Andreas Geiger, Jingyi Yu, and Hao Su. 2022. TensoRF: Tensorial Radiance Fields. arXiv preprint arXiv:2203.09517 (2022)."},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.01386"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.bushor.2018.05.009"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-40651-0_12"},{"key":"e_1_3_2_1_8_1","volume-title":"Deepview: View synthesis with learned gradient descent. CVPR","author":"Flynn John","year":"2019","unstructured":"John Flynn , Michael Broxton , Paul Debevec , Matthew DuVall , Graham Fyffe , Ryan Overbeck , Noah Snavely , and Richard Tucker . 2019 . Deepview: View synthesis with learned gradient descent. CVPR (2019). John Flynn, Michael Broxton, Paul Debevec, Matthew DuVall, Graham Fyffe, Ryan Overbeck, Noah Snavely, and Richard Tucker. 2019. Deepview: View synthesis with learned gradient descent. CVPR (2019)."},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00491"},{"key":"e_1_3_2_1_10_1","volume-title":"Multiple view geometry in computer vision","author":"Hartley Richard","unstructured":"Richard Hartley and Andrew Zisserman . 2003. Multiple view geometry in computer vision . Cambridge university press . Richard Hartley and Andrew Zisserman. 2003. Multiple view geometry in computer vision. Cambridge university press."},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00582"},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00604"},{"key":"e_1_3_2_1_13_1","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 18365--18375","author":"Johari Mohammad Mahdi","year":"2022","unstructured":"Mohammad Mahdi Johari , Yann Lepoittevin , and Fran\u00e7ois Fleuret . 2022 . Geonerf: Generalizing nerf with geometry priors . In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 18365--18375 . Mohammad Mahdi Johari, Yann Lepoittevin, and Fran\u00e7ois Fleuret. 2022. Geonerf: Generalizing nerf with geometry priors. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 18365--18375."},{"key":"e_1_3_2_1_14_1","volume-title":"Ramulator: A fast and extensible DRAM simulator","author":"Kim Yoongu","year":"2015","unstructured":"Yoongu Kim , Weikun Yang , and Onur Mutlu . 2015 . Ramulator: A fast and extensible DRAM simulator . IEEE Computer architecture letters 15, 1 (2015), 45--49. Yoongu Kim, Weikun Yang, and Onur Mutlu. 2015. Ramulator: A fast and extensible DRAM simulator. IEEE Computer architecture letters 15, 1 (2015), 45--49."},{"key":"e_1_3_2_1_15_1","volume-title":"RT-NeRF: Real-Time On-Device Neural Radiance Fields Towards Immersive AR\/VR Rendering. In 2022 IEEE\/ACM International Conference on Computer-Aided Design.","author":"Li Chaojian","year":"2022","unstructured":"Chaojian Li , Sixu Li , Yang Zhao , Wenbo Zhu , and Yingyan Lin . 2022 . RT-NeRF: Real-Time On-Device Neural Radiance Fields Towards Immersive AR\/VR Rendering. In 2022 IEEE\/ACM International Conference on Computer-Aided Design. Chaojian Li, Sixu Li, Yang Zhao, Wenbo Zhu, and Yingyan Lin. 2022. RT-NeRF: Real-Time On-Device Neural Radiance Fields Towards Immersive AR\/VR Rendering. In 2022 IEEE\/ACM International Conference on Computer-Aided Design."},{"key":"e_1_3_2_1_16_1","volume-title":"Neural Scene Flow Fields for Space-Time View Synthesis of Dynamic Scenes. CVPR","author":"Li Zhengqi","year":"2021","unstructured":"Zhengqi Li , Simon Niklaus , Noah Snavely , and Oliver Wang . 2021. Neural Scene Flow Fields for Space-Time View Synthesis of Dynamic Scenes. CVPR ( 2021 ). Zhengqi Li, Simon Niklaus, Noah Snavely, and Oliver Wang. 2021. Neural Scene Flow Fields for Space-Time View Synthesis of Dynamic Scenes. CVPR (2021)."},{"key":"e_1_3_2_1_17_1","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 7824--7833","author":"Liu Yuan","year":"2022","unstructured":"Yuan Liu , Sida Peng , Lingjie Liu , Qianqian Wang , Peng Wang , Christian Theobalt , Xiaowei Zhou , and Wenping Wang . 2022 . Neural rays for occlusion-aware image-based rendering . In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 7824--7833 . Yuan Liu, Sida Peng, Lingjie Liu, Qianqian Wang, Peng Wang, Christian Theobalt, Xiaowei Zhou, and Wenping Wang. 2022. Neural rays for occlusion-aware image-based rendering. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 7824--7833."},{"key":"e_1_3_2_1_18_1","volume-title":"Meta Quest Pro. www.meta.com\/quest\/quest-pro\/#overview","year":"2022","unstructured":"Meta. 2022. Meta Quest Pro. www.meta.com\/quest\/quest-pro\/#overview , 2022 -11-01. Meta. 2022. Meta Quest Pro. www.meta.com\/quest\/quest-pro\/#overview, 2022-11-01."},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1145\/3306346.3322980"},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58452-8_24"},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.3390\/encyclopedia2010031"},{"key":"e_1_3_2_1_22_1","unstructured":"NVIDIA Inc. 2021. NVIDIA Jetson TX2. https:\/\/www.nvidia.com\/en-us\/autonomous-machines\/embedded-systems\/jetson-tx2\/ accessed 2020-09-01.  NVIDIA Inc. 2021. NVIDIA Jetson TX2. https:\/\/www.nvidia.com\/en-us\/autonomous-machines\/embedded-systems\/jetson-tx2\/ accessed 2020-09-01."},{"key":"e_1_3_2_1_23_1","unstructured":"NVIDIA LLC. [n. d.]. Cuda C++ Programming Guide. https:\/\/docs.nvidia.com\/cuda\/cuda-c-programming-guide\/index.html#features-and-technical-specifications__technical-specifications-per-compute-capability.  NVIDIA LLC. [n. d.]. Cuda C++ Programming Guide. https:\/\/docs.nvidia.com\/cuda\/cuda-c-programming-guide\/index.html#features-and-technical-specifications__technical-specifications-per-compute-capability."},{"key":"e_1_3_2_1_24_1","volume-title":"GeForce RTX 2080 TI Graphics Card | NVIDIA. https:\/\/www.nvidia.com\/en-me\/geforce\/graphics-cards\/rtx-2080-ti\/, accessed 2020-09-01","author":"NVIDIA","year":"2021","unstructured":"NVIDIA LLC. 2021 . GeForce RTX 2080 TI Graphics Card | NVIDIA. https:\/\/www.nvidia.com\/en-me\/geforce\/graphics-cards\/rtx-2080-ti\/, accessed 2020-09-01 . NVIDIA LLC. 2021. GeForce RTX 2080 TI Graphics Card | NVIDIA. https:\/\/www.nvidia.com\/en-me\/geforce\/graphics-cards\/rtx-2080-ti\/, accessed 2020-09-01."},{"key":"e_1_3_2_1_25_1","volume-title":"Neural Scene Graphs for Dynamic Scenes. CVPR","author":"Ost Julian","year":"2021","unstructured":"Julian Ost , Fahim Mannan , Nils Thuerey , Julian Knodt , and Felix Heide . 2021. Neural Scene Graphs for Dynamic Scenes. CVPR ( 2021 ). Julian Ost, Fahim Mannan, Nils Thuerey, Julian Knodt, and Felix Heide. 2021. Neural Scene Graphs for Dynamic Scenes. CVPR (2021)."},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00025"},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00581"},{"key":"e_1_3_2_1_28_1","volume-title":"Hypernerf: A higher-dimensional representation for topologically varying neural radiance fields. arXiv preprint arXiv:2106.13228","author":"Park Keunhong","year":"2021","unstructured":"Keunhong Park , Utkarsh Sinha , Peter Hedman , Jonathan T Barron , Sofien Bouaziz , Dan B Goldman , Ricardo Martin-Brualla , and Steven M Seitz . 2021 . Hypernerf: A higher-dimensional representation for topologically varying neural radiance fields. arXiv preprint arXiv:2106.13228 (2021). Keunhong Park, Utkarsh Sinha, Peter Hedman, Jonathan T Barron, Sofien Bouaziz, Dan B Goldman, Ricardo Martin-Brualla, and Steven M Seitz. 2021. Hypernerf: A higher-dimensional representation for topologically varying neural radiance fields. arXiv preprint arXiv:2106.13228 (2021)."},{"key":"e_1_3_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01018"},{"key":"e_1_3_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.1145\/3550454.3555505"},{"key":"e_1_3_2_1_31_1","volume-title":"Proceedings of the IEEE\/CVF International Conference on Computer Vision. 10901--10911","author":"Reizenstein Jeremy","year":"2021","unstructured":"Jeremy Reizenstein , Roman Shapovalov , Philipp Henzler , Luca Sbordone , Patrick Labatut , and David Novotny . 2021 . Common objects in 3d: Large-scale learning and evaluation of real-life 3d category reconstruction . In Proceedings of the IEEE\/CVF International Conference on Computer Vision. 10901--10911 . Jeremy Reizenstein, Roman Shapovalov, Philipp Henzler, Luca Sbordone, Patrick Labatut, and David Novotny. 2021. Common objects in 3d: Large-scale learning and evaluation of real-life 3d category reconstruction. In Proceedings of the IEEE\/CVF International Conference on Computer Vision. 10901--10911."},{"key":"e_1_3_2_1_32_1","unstructured":"Google Research. [n. d.]. Google Scanned Objects. https:\/\/app.ignitionrobotics.org\/GoogleResearch\/fuel\/collections\/GoogleScannedObjects.  Google Research. [n. d.]. Google Scanned Objects. https:\/\/app.ignitionrobotics.org\/GoogleResearch\/fuel\/collections\/GoogleScannedObjects."},{"key":"e_1_3_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58529-7_37"},{"key":"e_1_3_2_1_34_1","volume-title":"GRAF: Generative radiance fields for 3D-aware image synthesis. NeurIPS","author":"Schwarz Katja","year":"2020","unstructured":"Katja Schwarz , Yiyi Liao , Michael Niemeyer , and Andreas Geiger . 2020 . GRAF: Generative radiance fields for 3D-aware image synthesis. NeurIPS (2020). Katja Schwarz, Yiyi Liao, Michael Niemeyer, and Andreas Geiger. 2020. GRAF: Generative radiance fields for 3D-aware image synthesis. NeurIPS (2020)."},{"key":"e_1_3_2_1_35_1","volume-title":"Real-time digital holographic microscopy using the graphic processing unit. Optics express 16, 16","author":"Shimobaba Tomoyoshi","year":"2008","unstructured":"Tomoyoshi Shimobaba , Yoshikuni Sato , Junya Miura , Mai Takenouchi , and Tomoyoshi Ito . 2008. Real-time digital holographic microscopy using the graphic processing unit. Optics express 16, 16 ( 2008 ), 11776--11781. Tomoyoshi Shimobaba, Yoshikuni Sato, Junya Miura, Mai Takenouchi, and Tomoyoshi Ito. 2008. Real-time digital holographic microscopy using the graphic processing unit. Optics express 16, 16 (2008), 11776--11781."},{"key":"e_1_3_2_1_36_1","volume-title":"Deepvoxels: Learning persistent 3d feature embeddings. CVPR","author":"Sitzmann Vincent","year":"2019","unstructured":"Vincent Sitzmann , Justus Thies , Felix Heide , Matthias Nie\u00dfner , Gordon Wetzstein , and Michael Zollhofer . 2019 . Deepvoxels: Learning persistent 3d feature embeddings. CVPR (2019). Vincent Sitzmann, Justus Thies, Felix Heide, Matthias Nie\u00dfner, Gordon Wetzstein, and Michael Zollhofer. 2019. Deepvoxels: Learning persistent 3d feature embeddings. CVPR (2019)."},{"key":"e_1_3_2_1_37_1","volume-title":"A primer for the Monte Carlo method","author":"Sobol Ilya M","unstructured":"Ilya M Sobol . 2018. A primer for the Monte Carlo method . CRC press . Ilya M Sobol. 2018. A primer for the Monte Carlo method. CRC press."},{"key":"e_1_3_2_1_38_1","volume-title":"Barron","author":"Srinivasan Pratul P.","year":"2021","unstructured":"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. CVPR ( 2021). 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. CVPR (2021)."},{"key":"e_1_3_2_1_39_1","first-page":"24261","article-title":"Mlp-mixer: An all-mlp architecture for vision","volume":"34","author":"Tolstikhin Ilya O","year":"2021","unstructured":"Ilya O Tolstikhin , Neil Houlsby , Alexander Kolesnikov , Lucas Beyer , Xiaohua Zhai , Thomas Unterthiner , Jessica Yung , Andreas Steiner , Daniel Keysers , Jakob Uszkoreit , 2021 . Mlp-mixer: An all-mlp architecture for vision . Advances in Neural Information Processing Systems 34 (2021), 24261 -- 24272 . Ilya O Tolstikhin, Neil Houlsby, Alexander Kolesnikov, Lucas Beyer, Xiaohua Zhai, Thomas Unterthiner, Jessica Yung, Andreas Steiner, Daniel Keysers, Jakob Uszkoreit, et al. 2021. Mlp-mixer: An all-mlp architecture for vision. Advances in Neural Information Processing Systems 34 (2021), 24261--24272.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_1_40_1","volume-title":"Attention is all you need. Advances in neural information processing systems 30","author":"Vaswani Ashish","year":"2017","unstructured":"Ashish Vaswani , Noam Shazeer , Niki Parmar , Jakob Uszkoreit , Llion Jones , Aidan N Gomez , \u0141ukasz Kaiser , and Illia Polosukhin . 2017. Attention is all you need. Advances in neural information processing systems 30 ( 2017 ). Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, \u0141ukasz Kaiser, and Illia Polosukhin. 2017. Attention is all you need. Advances in neural information processing systems 30 (2017)."},{"key":"e_1_3_2_1_41_1","volume-title":"2022 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 5481--5490","author":"Verbin Dor","year":"2022","unstructured":"Dor Verbin , Peter Hedman , Ben Mildenhall , Todd Zickler , Jonathan T Barron , and Pratul P Srinivasan . 2022 . Ref-nerf: Structured view-dependent appearance for neural radiance fields . In 2022 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 5481--5490 . Dor Verbin, Peter Hedman, Ben Mildenhall, Todd Zickler, Jonathan T Barron, and Pratul P Srinivasan. 2022. Ref-nerf: Structured view-dependent appearance for neural radiance fields. In 2022 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 5481--5490."},{"key":"e_1_3_2_1_42_1","unstructured":"Peihao Wang Xuxi Chen Tianlong Chen Subhashini Venugopalan Zhangyang Wang etal 2022. Is Attention All NeRF Needs? arXiv preprint arXiv:2207.13298 (2022).  Peihao Wang Xuxi Chen Tianlong Chen Subhashini Venugopalan Zhangyang Wang et al. 2022. Is Attention All NeRF Needs? arXiv preprint arXiv:2207.13298 (2022)."},{"key":"e_1_3_2_1_43_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00466"},{"key":"e_1_3_2_1_44_1","volume-title":"SinNeRF: Training Neural Radiance Fields on Complex Scenes from a Single Image. arXiv preprint arXiv:2204.00928","author":"Xu Dejia","year":"2022","unstructured":"Dejia Xu , Yifan Jiang , Peihao Wang , Zhiwen Fan , Humphrey Shi , and Zhangyang Wang . 2022. SinNeRF: Training Neural Radiance Fields on Complex Scenes from a Single Image. arXiv preprint arXiv:2204.00928 ( 2022 ). Dejia Xu, Yifan Jiang, Peihao Wang, Zhiwen Fan, Humphrey Shi, and Zhangyang Wang. 2022. SinNeRF: Training Neural Radiance Fields on Complex Scenes from a Single Image. arXiv preprint arXiv:2204.00928 (2022)."},{"key":"e_1_3_2_1_45_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00536"},{"key":"e_1_3_2_1_46_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00455"},{"key":"e_1_3_2_1_47_1","volume-title":"International journal of computer vision 27, 2","author":"Zhang Zhengyou","year":"1998","unstructured":"Zhengyou Zhang . 1998. Determining the epipolar geometry and its uncertainty: A review . International journal of computer vision 27, 2 ( 1998 ), 161--195. Zhengyou Zhang. 1998. Determining the epipolar geometry and its uncertainty: A review. International journal of computer vision 27, 2 (1998), 161--195."},{"key":"e_1_3_2_1_48_1","doi-asserted-by":"publisher","DOI":"10.1109\/ISCA45697.2020.00030"},{"key":"e_1_3_2_1_49_1","volume-title":"An RRAM-based Neural Radiance Field Processor. In 2022 IEEE 35th International System-on-Chip Conference (SOCC). IEEE, 1--5.","author":"Zheng Yueyang","year":"2022","unstructured":"Yueyang Zheng , Chaolin Rao , Haochuan Wan , Yuliang Zhou , Pingqiang Zhou , Jingyi Yu , and Xin Lou . 2022 . An RRAM-based Neural Radiance Field Processor. In 2022 IEEE 35th International System-on-Chip Conference (SOCC). IEEE, 1--5. Yueyang Zheng, Chaolin Rao, Haochuan Wan, Yuliang Zhou, Pingqiang Zhou, Jingyi Yu, and Xin Lou. 2022. An RRAM-based Neural Radiance Field Processor. In 2022 IEEE 35th International System-on-Chip Conference (SOCC). IEEE, 1--5."},{"key":"e_1_3_2_1_50_1","volume-title":"Stereo Magnification: Learning View Synthesis using Multiplane Images. SIGGRAPH","author":"Zhou Tinghui","year":"2018","unstructured":"Tinghui Zhou , Richard Tucker , John Flynn , Graham Fyffe , and Noah Snavely . 2018 . Stereo Magnification: Learning View Synthesis using Multiplane Images. SIGGRAPH (2018). Tinghui Zhou, Richard Tucker, John Flynn, Graham Fyffe, and Noah Snavely. 2018. Stereo Magnification: Learning View Synthesis using Multiplane Images. SIGGRAPH (2018)."}],"event":{"name":"ISCA '23: 50th Annual International Symposium on Computer Architecture","location":"Orlando FL USA","acronym":"ISCA '23","sponsor":["SIGARCH ACM Special Interest Group on Computer Architecture","IEEE"]},"container-title":["Proceedings of the 50th Annual International Symposium on Computer Architecture"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3579371.3589109","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T16:46:40Z","timestamp":1750178800000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3579371.3589109"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,6,17]]},"references-count":50,"alternative-id":["10.1145\/3579371.3589109","10.1145\/3579371"],"URL":"https:\/\/doi.org\/10.1145\/3579371.3589109","relation":{},"subject":[],"published":{"date-parts":[[2023,6,17]]},"assertion":[{"value":"2023-06-17","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}