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Recovering a dense depth image from sparse LiDAR scans is a challenging task.
Learning guided convolutional network for depth completion
Tang, J.; Tian, F.-P.; Feng, W.; Li, J.; and Tan, P. 2019 · 1908
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Non-Local Spatial Propagation Network for Depth Completion
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Deep ordinal regression network for monocular depth estimation
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Dense disparity maps from sparse disparity measurements
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Deep convolutional neural fields for depth estimation from a single image
Liu, F.; Shen, C.; and Lin, G. 2015 · 2015
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Fully convolutional networks for semantic segmentation
Long, J.; Shelhamer, E.; and Darrell, T. 2015 · 2015
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U-net: Convolutional networks for biomedical image segmentation
Ronneberger, O.; Fischer, P.; and Brox, T. 2015 · 2015
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Chen, W.; Fu, Z.; Yang, D.; and Deng, J. 2016 · 2016
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He, K.; Zhang, X.; Ren, S.; and Sun, J. 2016 · 2016
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Lee, C.; and Chung, K.-S. 2019 · 2019
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Ma, F.; Cavalheiro, G. V.; and Karaman, S. 2019 · 2019
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Deeplidar: Deep surface normal guided depth prediction for outdoor scene from sparse lidar data and single color image
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Singan: Learning a generative model from a single natural image
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Sparse and noisy lidar completion with rgb guidance and uncertainty
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Sajjadi, M. S.; Scholkopf, B.; and Hirsch, M. 2017 · 2017
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Sparsity invariant cnns
Uhrig, J.; Schneider, N.; Schneider, L.; Franke, U.; Brox, T.; and Geiger, A. 2017 · 2017
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In defense of classical image processing: Fast depth completion on the cpu
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Image super-resolution using very deep residual channel attention networks
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Learning joint 2d-3d representations for depth completion
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Pseudo-lidar from visual depth estimation: Bridging the gap in 3d object detection for autonomous driving
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Bilateral cyclic constraint and adaptive regularization for unsupervised monocular depth prediction
Wong, A.; and Soatto, S. 2019 · 2019
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Depth completion from sparse lidar data with depth-normal constraints
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Data uncertainty learning in face recognition
Chang, J.; Lan, Z.; Cheng, C.; and Wei, Y. 2020 · 2020
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CSPN++: Learning Context and Resource Aware Convolutional Spatial Propagation Networks for Depth Completion
Cheng, X.; Wang, P.; Guan, C.; and Yang, R. 2020 · 2020
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Learning guided convolutional network for depth completion
Tang, J.; Tian, F.-P.; Feng, W.; Li, J.; and Tan, P. 2020 · 2020
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An Adaptive Framework for Learning Unsupervised Depth Completion
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Adaptive deconvolutional networks for mid and high level feature learning
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