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A recent strand of work in view synthesis uses deep learning to generate multiplane images (a camera-centric, layered 3D representation) given two or more input images at known viewpoints.
Compositing digital images
Thomas Porter and Tom Duff · 1984
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Visual integration and detection of discontinuities: The key role of intensity edges
Ed Gamble and Tomaso Poggio · 1987
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The lumigraph
Steven J. Gortler, Radek Grzeszczuk, Richard Szeliski, and Michael F. Cohen · 1996
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Light field rendering
Marc Levoy and Pat Hanrahan · 1996
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Layered depth images
Jonathan Shade, Steven Gortler, Li-wei He, and Richard Szeliski · 1998
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Stereo matching with transparency and matting
Richard Szeliski and Polina Golland · 1999
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A taxonomy and evaluation of dense two-frame stereo correspondence algorithms
Daniel Scharstein and Richard Szeliski · 2002
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High-quality video view interpolation using a layered representation
C. Lawrence Zitnick, Sing Bing Kang, Matthew Uyttendaele, Simon Winder, and Richard Szeliski · 2004
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Layered photo pop-up
Lech Świrski, Christian Richardt, and Neil A. Dodgson · 2011
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Depth synthesis and local warps for plausible image-based navigation
Gaurav Chaurasia, Sylvain Duchêne, Olga Sorkine-Hornung, and George Drettakis · 2013
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Vision meets robotics: The KITTI dataset
Andreas Geiger, Philip Lenz, Christoph Stiller, and Raquel Urtasun · 2013
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Depth map prediction from a single image using a multi-scale deep network
David Eigen, Christian Puhrsch, and Rob Fergus · 2014
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Adam: A method for stochastic optimization
Diederik P. Kingma and Jimmy Ba · 2014
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DeepStereo: Learning to predict new views from the world’s imagery
John Flynn, Ivan Neulander, James Philbin, and Noah Snavely · 2016
Cited alongside, same era.
Unsupervised CNN for single view depth estimation: Geometry to the rescue
Ravi Garg, Vijay Kumar BG, Gustavo Carneiro, and Ian Reid · 2016
Cited alongside, same era.
Learning-based view synthesis for light field cameras
Nima Khademi Kalantari, Ting-Chun Wang, and Ravi Ramamoorthi · 2016
Cited alongside, same era.
N. Mayer, E. Ilg, P. Häusser, P. Fischer, D. Cremers, A. Dosovitskiy, and T. Brox · 2016
Cited alongside, same era.
Deep3D: Fully automatic 2D-to-3D video conversion with deep convolutional neural networks
Junyuan Xie, Ross Girshick, and Ali Farhadi · 2016
Cited alongside, same era.
Geometry-aware deep network for single-image novel view synthesis
Miaomiao Liu, Xuming He, and Mathieu Salzmann · 2018
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Layer-structured 3D scene inference via view synthesis
Shubham Tulsiani, Richard Tucker, and Noah Snavely · 2018
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Learning depth from monocular videos using direct methods
Chaoyang Wang, José Miguel Buenaposada, Rui Zhu, and Simon Lucey · 2018
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The unreasonable effectiveness of deep features as a perceptual metric
Richard Zhang, Phillip Isola, Alexei A. Efros, Eli Shechtman, and Oliver Wang · 2018
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Stereo magnification: Learning view synthesis using multiplane images
Tinghui Zhou, Richard Tucker, John Flynn, Graham Fyffe, and Noah Snavely · 2018
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Learning single-image depth from videos using quality assessment networks
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Unsupervised monocular depth estimation with left-right consistency
Clément Godard, Oisin Mac Aodha, and Gabriel J Brostow · 2017
Cited alongside, same era.
Soft 3D reconstruction for view synthesis
Eric Penner and Li Zhang · 2017
Cited alongside, same era.
Learning to synthesize a 4D RGBD light field from a single image
Pratul P. Srinivasan, Tongzhou Wang, Ashwin Sreelal, Ravi Ramamoorthi, and Ren Ng · 2017
Cited alongside, same era.
Demon: Depth and motion network for learning monocular stereo
Benjamin Ummenhofer, Huizhong Zhou, Jonas Uhrig, Nikolaus Mayer, Eddy Ilg, Alexey Dosovitskiy, and Thomas Brox · 2017
Cited alongside, same era.
Unsupervised learning of depth and ego-motion from video
Tinghui Zhou, Matthew Brown, Noah Snavely, and David G. Lowe · 2017
Cited alongside, same era.
Deep blending for free-viewpoint image-based rendering
Peter Hedman, Julien Philip, True Price, Jan-Michael Frahm, George Drettakis, and Gabriel Brostow · 2018
Cited alongside, same era.
Evaluation of CNN-based single-image depth estimation methods
Tobias Koch, Lukas Liebel, Friedrich Fraundorfer, and Marco Körner · 2018
Cited alongside, same era.
Weifeng Chen, Shengyi Qian, and Jia Deng · 2019
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Deepview: View synthesis with learned gradient descent
John Flynn, Michael Broxton, Paul Debevec, Matthew DuVall, Graham Fyffe, Ryan Overbeck, Noah Snavely, and Richard Tucker · 2019
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Towards robust monocular depth estimation: Mixing datasets for zero-shot cross-dataset transfer
Katrin Lasinger, René Ranftl, Konrad Schindler, and Vladlen Koltun · 2019
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Learning the depths of moving people by watching frozen people
Zhengqi Li, Tali Dekel, Forrester Cole, Richard Tucker, Noah Snavely, Ce Liu, and William T. Freeman · 2019
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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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3D Ken Burns effect from a single image
Simon Niklaus, Long Mai, Jimei Yang, and Feng Liu · 2019
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Pushing the boundaries of view extrapolation with multiplane images
Pratul P. Srinivasan, Richard Tucker, Jonathan T. Barron, Ravi Ramamoorthi, Ren Ng, and Noah Snavely · 2019
Later among the works it cites.