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With the rise of data driven deep neural networks as a realization of universal function approximators, most research on computer vision problems has moved away from hand crafted classical image processing algorithms.
On estimating regression
Elizbar A Nadaraya · 1964
Earlier work this paper cites.
The manhattan world assumption: Regularities in scene statistics which enable bayesian inference
James M Coughlan and Alan L Yuille · 2001
Earlier work this paper cites.
A noise-aware filter for real-time depth upsampling
Derek Chan, Hylke Buisman, Christian Theobalt, and Sebastian Thrun · 2008
Earlier work this paper cites.
Temporal filtering for depth maps generated by kinect depth camera
Sergey Matyunin, Dmitriy Vatolin, Yury Berdnikov, and Maxim Smirnov · 2011
Earlier work this paper cites.
Are we ready for autonomous driving? the kitti vision benchmark suite
Andreas Geiger, Philip Lenz, and Raquel Urtasun · 2012
Earlier work this paper cites.
Ai-complete, ai-hard, or ai-easy-classification of problems in ai
Roman V Yampolskiy · 2012
Earlier work this paper cites.
Depth image enhancement for kinect using region growing and bilateral filter
Li Chen, Hui Lin, and Shutao Li · 2012
Earlier work this paper cites.
Coherent spatiotemporal filtering, upsampling and rendering of rgbz videos
Christian Richardt, Carsten Stoll, Neil A Dodgson, Hans-Peter Seidel, and Christian Theobalt · 2012
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Structure guided fusion for depth map inpainting
Fei Qi, Junyu Han, Pengjin Wang, Guangming Shi, and Fu Li · 2013
Cited alongside, same era.
Depth super resolution by rigid body self-similarity in 3d
Michael Hornácek, Christoph Rhemann, Margrit Gelautz, and Carsten Rother · 2013
Cited alongside, same era.
Hengshuang Zhao, Jianping Shi, Xiaojuan Qi, Xiaogang Wang, and Jiaya Jia · 2016
Cited alongside, same era.
End to end learning for self-driving cars
Mariusz Bojarski, Davide Del Testa, Daniel Dworakowski, Bernhard Firner, Beat Flepp, Prasoon Goyal, Lawrence D Jackel, Mathew Monfort, Urs Muller, Jiakai Zhang, et al · 2016
Cited alongside, same era.
Deep depth super-resolution: Learning depth super-resolution using deep convolutional neural network
Xibin Song, Yuchao Dai, and Xueying Qin · 2016
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Joint 3d proposal generation and object detection from view aggregation
Jason Ku, Melissa Mozifian, Jungwook Lee, Ali Harakeh, and Steven Waslander · 2017
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Multi-view 3d object detection network for autonomous driving
Xiaozhi Chen, Huimin Ma, Ji Wan, Bo Li, and Tian Xia · 2017
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Frustum pointnets for 3d object detection from rgb-d data
Charles R Qi, Wei Liu, Chenxia Wu, Hao Su, and Leonidas J Guibas · 2017
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Jonas Uhrig, Nick Schneider, Lukas Schneider, Uwe Franke, Thomas Brox, and Andreas Geiger · 2017
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Depth map super-resolution by deep multi-scale guidance
Tak-Wai Hui, Chen Change Loy, and Xiaoou Tang · 2016
Cited alongside, same era.
http://www.cvlibs.net/datasets/kitti/eval_depth.php?benchmark=depth_completion
Kitti Depth Completion Benchmark
Cited in the paper.
https://opencv.org/
Open Source Computer Vision Library
Cited in the paper.
http://www.numpy.org/index.html
NumPy
Cited in the paper.
Later among the works it cites.
Voxelnet: End-to-end learning for point cloud based 3d object detection
Yin Zhou and Oncel Tuzel · 2017
Later among the works it cites.