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We introduce VA-DepthNet, a simple, effective, and accurate deep neural network approach for the single-image depth prediction (SIDP) problem.
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David Nistér · 2004
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Derek Hoiem, Alexei A Efros, and Martial Hebert · 2005
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Ashutosh Saxena, Min Sun, and Andrew Y Ng · 2007
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Make3d: Learning 3d scene structure from a single still image
Ashutosh Saxena, Min Sun, and Andrew Y Ng · 2008
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Imagenet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
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Accurate, dense, and robust multiview stereopsis
Yasutaka Furukawa and Jean Ponce · 2009
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An introduction to total variation for image analysis
Antonin Chambolle, Vicent Caselles, Daniel Cremers, Matteo Novaga, and Thomas Pock · 2010
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Are we ready for autonomous driving? the kitti vision benchmark suite
Andreas Geiger, Philip Lenz, and Raquel Urtasun · 2012
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Imagenet classification with deep convolutional neural networks
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton · 2012
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Individual choice behavior: A theoretical analysis
R Duncan Luce · 2012
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Nathan Silberman, Derek Hoiem, Pushmeet Kohli, and Rob Fergus · 2012
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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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Depth and surface normal estimation from monocular images using regression on deep features and hierarchical crfs
Bo Li, Chunhua Shen, Yuchao Dai, Anton van den Hengel, and Mingyi He · 2015
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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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Very deep convolutional networks for large-scale image recognition
Karen Simonyan and Andrew Zisserman · 2015
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Sun rgb-d: A rgb-d scene understanding benchmark suite
Shuran Song, Samuel P Lichtenberg, and Jianxiong Xiao · 2015
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Single-image depth perception in the wild
Weifeng Chen, Zhao Fu, Dawei Yang, and Jia Deng · 2016
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Sublabel-accurate relaxation of nonconvex energies
Thomas Mollenhoff, Emanuel Laude, Michael Moeller, Jan Lellmann, and Daniel Cremers · 2016
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Instance normalization: The missing ingredient for fast stylization
Dmitry Ulyanov, Andrea Vedaldi, and Victor Lempitsky · 2016
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Monocular dense 3d reconstruction of a complex dynamic scene from two perspective frames
Suryansh Kumar, Yuchao Dai, and Hongdong Li · 2017
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A two-streamed network for estimating fine-scaled depth maps from single rgb images
Jun Li, Reinhard Klein, and Angela Yao · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
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Depth estimation via affinity learned with convolutional spatial propagation network
Xinjing Cheng, Peng Wang, and Ruigang Yang · 2018
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Towards robust monocular depth estimation: Mixing datasets for zero-shot cross-dataset transfer
René Ranftl, Katrin Lasinger, David Hafner, Konrad Schindler, and Vladlen Koltun · 2020
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Structure-guided ranking loss for single image depth prediction
Ke Xian, Jianming Zhang, Oliver Wang, Long Mai, Zhe Lin, and Zhiguo Cao · 2020
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D3vo: Deep depth, deep pose and deep uncertainty for monocular visual odometry
Nan Yang, Lukas von Stumberg, Rui Wang, and Daniel Cremers · 2020
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Bidirectional attention network for monocular depth estimation
Shubhra Aich, Jean Marie Uwabeza Vianney, Md Amirul Islam, and Mannat Kaur Bingbing Liu · 2021
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Adabins: Depth estimation using adaptive bins
Shariq Farooq Bhat, Ibraheem Alhashim, and Peter Wonka · 2021
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Transformer-based monocular depth estimation with attention supervision
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Huan Fu, Mingming Gong, Chaohui Wang, Kayhan Batmanghelich, and Dacheng Tao · 2018
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Deepmvs: Learning multi-view stereopsis
Po-Han Huang, Kevin Matzen, Johannes Kopf, Narendra Ahuja, and Jia-Bin Huang · 2018
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Geonet: Geometric neural network for joint depth and surface normal estimation
Xiaojuan Qi, Renjie Liao, Zhengzhe Liu, Raquel Urtasun, and Jiaya Jia · 2018
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Revisiting single image depth estimation: Toward higher resolution maps with accurate object boundaries
Junjie Hu, Mete Ozay, Yan Zhang, and Takayuki Okatani · 2019
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Superpixel soup: Monocular dense 3d reconstruction of a complex dynamic scene
Suryansh Kumar, Yuchao Dai, and Hongdong Li · 2019
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Rtab-map as an open-source lidar and visual simultaneous localization and mapping library for large-scale and long-term online operation
Mathieu Labbé and François Michaud · 2019
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Monocular depth estimation using relative depth maps
Jae-Han Lee and Chang-Su Kim · 2019
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Wenjie Chang, Yueyi Zhang, and Zhiwei Xiong · 2021
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An image is worth 16x16 words: Transformers for image recognition at scale
Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, Jakob Uszkoreit, and Neil Houlsby · 2021
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Patch-wise attention network for monocular depth estimation
Sihaeng Lee, Janghyeon Lee, Byungju Kim, Eojindl Yi, and Junmo Kim · 2021
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Monocular depth estimation via listwise ranking using the plackett-luce model
Julian Lienen, Eyke Hüllermeier, Ralph Ewerth, and Nils Nommensen · 2021
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Deep line encoding for monocular 3d object detection and depth prediction
Ce Liu, Shuhang Gu, Luc Van Gool, and Radu Timofte · 2021
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Adaptive surface normal constraint for depth estimation
Xiaoxiao Long, Cheng Lin, Lingjie Liu, Wei Li, Christian Theobalt, Ruigang Yang, and Wenping Wang · 2021
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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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Vip-deeplab: Learning visual perception with depth-aware video panoptic segmentation
Siyuan Qiao, Yukun Zhu, Hartwig Adam, Alan Yuille, and Liang-Chieh Chen · 2021
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Vision transformers for dense prediction
René Ranftl, Alexey Bochkovskiy, and Vladlen Koltun · 2021
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Droid-slam: Deep visual slam for monocular, stereo, and rgb-d cameras
Zachary Teed and Jia Deng · 2021
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Transformer-based attention networks for continuous pixel-wise prediction
Guanglei Yang, Hao Tang, Mingli Ding, Nicu Sebe, and Elisa Ricci · 2021
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Uncertainty-aware deep multi-view photometric stereo
Berk Kaya, Suryansh Kumar, Carlos Oliveira, Vittorio Ferrari, and Luc Van Gool · 2022
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A convnet for the 2020s
Zhuang Liu, Hanzi Mao, Chao-Yuan Wu, Christoph Feichtenhofer, Trevor Darrell, and Saining Xie · 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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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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