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In this paper we present a novel method to increase the spatial resolution of depth images.
Robust regression: Asymptotics, conjectures and monte carlo
Peter J. Huber · 1973
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James Diebel and Sebastian Thrun · 2005
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Johannes Kopf, Michael F. Cohen, Dani Lischinski, and Matthew Uyttendaele · 2007
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Spatial-Depth Super Resolution for Range Images
Qingxiong Yang, Ruigang Yang, James Davis, and David Nistér · 2007
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A Noise-aware Filter for Real-time Depth Upsampling
Derek Chan, Hylke Buisman, Christian Theobalt, and Sebastian Thrun · 2008
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G. Gilboa and S. Osher · 2009
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Efficient Regression of General-Activity Human Poses from Depth Images
Ross Girshick, Jamie Shotton, Pushmeet Kohli, Antonio Criminisi, and Andrew W. Fitzgibbon · 2011
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Real-time Human Pose Recognition in Parts from Single Depth Images
Jamie Shotton, Toby Sharp, Alex Kipman, Andrew Fitzgibbon, Mark Finocchio, Andrew Blake, Mat Cook, and Richard Moore · 2011
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Sergio Almansa-Valverde, José Carlos Castillo, and Antonio Fernández-Caballero · 2012
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Oisin Mac Aodha, Neill D.F. Campbell, Arun Nair, and Gabriel J. Brostow · 2012
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Danhang Tang, Hyung Jin Chang, Alykhan Tejani, and Tae-Kyun Kim · 2014
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A+: Adjusted Anchored Neighborhood Regression for Fast Super-Resolution
Radu Timofte, Vincent De Smet, and Luc Van Gool · 2014
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Color-Guided Depth Recovery From RGB-D Data Using an Adaptive Autoregressive Model
Jingyu Yang, Xinchen Ye, Kun Li, Chunping Hou, and Yao Wang · 2014
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Learning Deep Structured Models
Liang-Chieh Chen, Alexander G. Schwing, Alan L. Yuille, and Raquel Urtasun · 2015
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Variational Depth Superresolution using Example-Based Edge Representations
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Depth Super Resolution by Rigid Body Self-Similarity in 3D
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Data-Driven Depth Map Refinement via Multi-scale Spare Representations
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Fast and Accurate Image Upscaling with Super-Resolution Forests
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Deep Residual Learning for Image Recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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