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Training a Neural Radiance Field (NeRF) without pre-computed camera poses is challenging.
View interpolation for image synthesis
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Angela Dai, Angel X Chang, Manolis Savva, Maciej Halber, Thomas Funkhouser, and Matthias Nießner · 2017
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Arno Knapitsch, Jaesik Park, Qian-Yi Zhou, and Vladlen Koltun · 2017
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Tinghui Zhou, Matthew Brown, Noah Snavely, and David G Lowe · 2017
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Deep ordinal regression network for monocular depth estimation
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Shubham Tulsiani, Richard Tucker, and Noah Snavely · 2018
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Richard Zhang, Phillip Isola, Alexei A Efros, Eli Shechtman, and Oliver Wang · 2018
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A tutorial on quantitative trajectory evaluation for visual (-inertial) odometry
Zichao Zhang and Davide Scaramuzza · 2018
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Stereo magnification: Learning view synthesis using multiplane images
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Local light field fusion: Practical view synthesis with prescriptive sampling guidelines
Ben Mildenhall, Pratul P Srinivasan, Rodrigo Ortiz-Cayon, Nima Khademi Kalantari, Ravi Ramamoorthi, Ren Ng, and Abhishek Kar · 2019
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Towards robust monocular depth estimation: Mixing datasets for zero-shot cross-dataset transfer
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Chen Gao, Ayush Saraf, Johannes Kopf, and Jia-Bin Huang · 2021
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Fastnerf: High-fidelity neural rendering at 200fps
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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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Nerfingmvs: Guided optimization of neural radiance fields for indoor multi-view stereo
Yi Wei, Shaohui Liu, Yongming Rao, Wang Zhao, Jiwen Lu, and Jie Zhou · 2021
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Lior Yariv, Jiatao Gu, Yoni Kasten, and Yaron Lipman · 2021
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inerf: Inverting neural radiance fields for pose estimation
Lin Yen-Chen, Pete Florence, Jonathan T Barron, Alberto Rodriguez, Phillip Isola, and Tsung-Yi Lin · 2021
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pixelnerf: Neural radiance fields from one or few images
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Tensorf: Tensorial radiance fields
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Boosting monocular depth estimation models to high-resolution via content-adaptive multi-resolution merging
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