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Inferring a meaningful geometric scene representation from a single image is a fundamental problem in computer vision.
Ray tracing volume densities
James T Kajiya and Brian P Von Herzen · 1984
Earlier work this paper cites.
Optical models for direct volume rendering
Nelson Max · 1995
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Layered depth images
Jonathan Shade, Steven Gortler, Li-wei He, and Richard Szeliski · 1998
Earlier work this paper cites.
Image quality assessment: from error visibility to structural similarity
Zhou Wang, Alan C Bovik, Hamid R Sheikh, and Eero P Simoncelli · 2004
Earlier work this paper cites.
Indoor segmentation and support inference from rgbd images
Nathan Silberman, Derek Hoiem, Pushmeet Kohli, and Rob Fergus · 2012
Earlier work this paper cites.
Vision meets robotics: The kitti dataset
Andreas Geiger, Philip Lenz, Christoph Stiller, and Raquel Urtasun · 2013
Earlier work this paper cites.
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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Learning depth from single monocular images using deep convolutional neural fields
Fayao Liu, Chunhua Shen, Guosheng Lin, and Ian Reid · 2015
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Structure-from-motion revisited
Johannes Lutz Schönberger and Jan-Michael Frahm · 2016
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Pixelwise view selection for unstructured multi-view stereo
Johannes Lutz Schönberger, Enliang Zheng, Marc Pollefeys, and Jan-Michael Frahm · 2016
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View synthesis by appearance flow
Tinghui Zhou, Shubham Tulsiani, Weilun Sun, Jitendra Malik, and Alexei A Efros · 2016
Earlier work this paper cites.
Unsupervised monocular depth estimation with left-right consistency
Clément Godard, Oisin Mac Aodha, and Gabriel J Brostow · 2017
Earlier work this paper cites.
Semi-supervised deep learning for monocular depth map prediction
Yevhen Kuznietsov, Jorg Stuckler, and Bastian Leibe · 2017
Earlier work this paper cites.
Unsupervised learning of depth and ego-motion from video
Tinghui Zhou, Matthew Brown, Noah Snavely, and David G Lowe · 2017
Earlier work this paper cites.
Deep ordinal regression network for monocular depth estimation
Huan Fu, Mingming Gong, Chaohui Wang, Kayhan Batmanghelich, and Dacheng Tao · 2018
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Layer-structured 3d scene inference via view synthesis
Shubham Tulsiani, Richard Tucker, and Noah Snavely · 2018
Earlier work this paper cites.
Deep virtual stereo odometry: Leveraging deep depth prediction for monocular direct sparse odometry
Nan Yang, Rui Wang, Jorg Stuckler, and Daniel Cremers · 2018
Earlier work this paper cites.
Unsupervised learning of monocular depth estimation and visual odometry with deep feature reconstruction
Huangying Zhan, Ravi Garg, Chamara Saroj Weerasekera, Kejie Li, Harsh Agarwal, and Ian Reid · 2018
Earlier work this paper cites.
Stereo magnification: Learning view synthesis using multiplane images
Tinghui Zhou, Richard Tucker, John Flynn, Graham Fyffe, and Noah Snavely · 2018
Earlier work this paper cites.
Object-driven multi-layer scene decomposition from a single image
Helisa Dhamo, Nassir Navab, and Federico Tombari · 2019
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Peeking behind objects: Layered depth prediction from a single image
Helisa Dhamo, Keisuke Tateno, Iro Laina, Nassir Navab, and Federico Tombari · 2019
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Digging into self-supervised monocular depth estimation
Clément Godard, Oisin Mac Aodha, Michael Firman, and Gabriel J Brostow · 2019
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Every pixel counts++: Joint learning of geometry and motion with 3d holistic understanding
Chenxu Luo, Zhenheng Yang, Peng Wang, Yang Wang, Wei Xu, Ram Nevatia, and Alan Yuille · 2019
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Occupancy networks: Learning 3d reconstruction in function space
Lars Mescheder, Michael Oechsle, Michael Niemeyer, Sebastian Nowozin, and Andreas Geiger · 2019
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PyTorch: An Imperative Style, High-Performance Deep Learning Library
Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, Alban Desmaison, Andreas Kopf, Edward Yang, Zachary DeVito, Martin Raison, Alykhan Tejani, Sasank Chilamkurthy, Benoit Steiner, Lu Fang, Junjie Bai, and Soumith Chintala · 2019
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Nerf: Representing scenes as neural radiance fields for view synthesis
Ben Mildenhall, Pratul P Srinivasan, Matthew Tancik, Jonathan T Barron, Ravi Ramamoorthi, and Ren Ng · 2021
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Neural geometric level of detail: Real-time rendering with implicit 3d shapes
Towaki Takikawa, Joey Litalien, Kangxue Yin, Karsten Kreis, Charles Loop, Derek Nowrouzezahrai, Alec Jacobson, Morgan McGuire, and Sanja Fidler · 2021
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Monorec: Semi-supervised dense reconstruction in dynamic environments from a single moving camera
Felix Wimbauer, Nan Yang, Lukas Von Stumberg, Niclas Zeller, and Daniel Cremers · 2021
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pixelnerf: Neural radiance fields from one or few images
Alex Yu, Vickie Ye, Matthew Tancik, and Angjoo Kanazawa · 2021
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Mip-nerf 360: Unbounded anti-aliased neural radiance fields
Jonathan T Barron, Ben Mildenhall, Dor Verbin, Pratul P Srinivasan, and Peter Hedman · 2022
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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
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Self-supervised monocular depth hints
Jamie Watson, Michael Firman, Gabriel J Brostow, and Daniyar Turmukhambetov · 2019
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Forget about the lidar: Self-supervised depth estimators with med probability volumes
Juan Luis GonzalezBello and Munchurl Kim · 2020
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3d packing for self-supervised monocular depth estimation
Vitor Guizilini, Rares Ambrus, Sudeep Pillai, Allan Raventos, and Adrien Gaidon · 2020
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Neural sparse voxel fields
Lingjie Liu, Jiatao Gu, Kyaw Zaw Lin, Tat-Seng Chua, and Christian Theobalt · 2020
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Convolutional occupancy networks
Songyou Peng, Michael Niemeyer, Lars Mescheder, Marc Pollefeys, and Andreas Geiger · 2020
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Feature-metric loss for self-supervised learning of depth and egomotion
Chang Shu, Kun Yu, Zhixiang Duan, and Kuiyuan Yang · 2020
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Scenerf: Self-supervised monocular 3d scene reconstruction with radiance fields
Anh-Quan Cao and Raoul de Charette · 2022
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Tensorf: Tensorial radiance fields
Anpei Chen, Zexiang Xu, Andreas Geiger, Jingyi Yu, and Hao Su · 2022
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Depth-supervised nerf: Fewer views and faster training for free
Kangle Deng, Andrew Liu, Jun-Yan Zhu, and Deva Ramanan · 2022
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Infonerf: Ray entropy minimization for few-shot neural volume rendering
Mijeong Kim, Seonguk Seo, and Bohyung Han · 2022
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Zhenyu Li, Zehui Chen, Xianming Liu, and Junjun Jiang · 2022
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Binsformer: Revisiting adaptive bins for monocular depth estimation
Zhenyu Li, Xuyang Wang, Xianming Liu, and Junjun Jiang · 2022
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Kitti-360: A novel dataset and benchmarks for urban scene understanding in 2d and 3d
Yiyi Liao, Jun Xie, and Andreas Geiger · 2022
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Autorf: Learning 3d object radiance fields from single view observations
Norman Müller, Andrea Simonelli, Lorenzo Porzi, Samuel Rota Bulò, Matthias Nießner, and Peter Kontschieder · 2022
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Instant neural graphics primitives with a multiresolution hash encoding
Thomas Müller, Alex Evans, Christoph Schied, and Alexander Keller · 2022
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Regnerf: Regularizing neural radiance fields for view synthesis from sparse inputs
Michael Niemeyer, Jonathan T Barron, Ben Mildenhall, Mehdi SM Sajjadi, Andreas Geiger, and Noha Radwan · 2022
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Dense depth priors for neural radiance fields from sparse input views
Barbara Roessle, Jonathan T Barron, Ben Mildenhall, Pratul P Srinivasan, and Matthias Nießner · 2022
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Scene representation transformer: Geometry-free novel view synthesis through set-latent scene representations
Mehdi SM Sajjadi, Henning Meyer, Etienne Pot, Urs Bergmann, Klaus Greff, Noha Radwan, Suhani Vora, Mario Lučić, Daniel Duckworth, Alexey Dosovitskiy, et al · 2022
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Seeing 3d objects in a single image via self-supervised static-dynamic disentanglement
Prafull Sharma, Ayush Tewari, Yilun Du, Sergey Zakharov, Rares Ambrus, Adrien Gaidon, William T Freeman, Fredo Durand, Joshua B Tenenbaum, and Vincent Sitzmann · 2022
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De-rendering 3d objects in the wild
Felix Wimbauer, Shangzhe Wu, and Christian Rupprecht · 2022
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New crfs: Neural window fully-connected crfs for monocular depth estimation
Weihao Yuan, Xiaodong Gu, Zuozhuo Dai, Siyu Zhu, and Ping Tan · 2022
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Devnet: Self-supervised monocular depth learning via density volume construction
Kaichen Zhou, Lanqing Hong, Changhao Chen, Hang Xu, Chaoqiang Ye, Qingyong Hu, and Zhenguo Li · 2022
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