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This paper focuses on semantic scene completion, a task for producing a complete 3D voxel representation of volumetric occupancy and semantic labels for a scene from a single-view depth map observation.
Object recognition in 3D point clouds using web data and domain adaptation
K. Lai and D. Fox · 2010
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KinectFusion: Real-time dense surface mapping and tracking
R. A. Newcombe, S. Izadi, O. Hilliges, D. Molyneaux, D. Kim, A. J. Davison, P. Kohi, J. Shotton, S. Hodges, and A. Fitzgibbon · 2011
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Acquisition of 3D indoor environments with variability and repetition
Y. M. Kim, N. Mitra, D. Yan, and L. Guibas · 2012
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Acquiring 3D indoor environments with variability and repetition
Y. M. Kim, N. J. Mitra, D. Yan, and L. Guibas · 2012
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A search-classify approach for cluttered indoor scene understanding
L. Nan, K. Xie, and A. Sharf · 2012
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RGB-(D) scene labeling: Features and algorithms
X. Ren, L. Bo, and D. Fox · 2012
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Indoor segmentation and support inference from RGBD images
N. Silberman, D. Hoiem, P. Kohli, and R. Fergus · 2012
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Perceptual organization and recognition of indoor scenes from RGB-D images
S. Gupta, P. Arbelaez, and J. Malik · 2013
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Joint 3D scene reconstruction and class segmentation
C. Hane, C. Zach, A. Cohen, R. Angst, and M. Pollefeys · 2013
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A linear approach to matching cuboids in RGBD images
H. Jiang and J. Xiao · 2013
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3D scene understanding by Voxel-CRF
B.-s. Kim, P. Kohli, and S. Savarese · 2013
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Holistic scene understanding for 3D object detection with RGBD cameras
D. Lin, S. Fidler, and R. Urtasun · 2013
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Beyond point clouds: Scene understanding by reasoning geometry and physics
B. Zheng, Y. Zhao, J. C. Yu, K. Ikeuchi, and S.-C. Zhu · 2013
Cited alongside, same era.
Caffe: Convolutional architecture for fast feature embedding
Y. Jia, E. Shelhamer, J. Donahue, S. Karayev, J. Long, R. Girshick, S. Guadarrama, and T. Darrell · 2014
Cited alongside, same era.
Unsupervised feature learning for 3D scene labeling
K. Lai, L. Bo, and D. Fox · 2014
Cited alongside, same era.
Object detection and classification from large-scale cluttered indoor scans
O. Mattausch, D. Panozzo, C. Mura, O. Sorkine-Hornung, and R. Pajarola · 2014
Cited alongside, same era.
Sliding Shapes for 3D object detection in depth images
S. Song and J. Xiao · 2014
Cited alongside, same era.
VoxNet: A 3D convolutional neural network for real-time object recognition
D. Maturana and S. Scherer · 2015
Later among the works it cites.
Rapter: Rebuilding man-made scenes with regular arrangements of planes
A. Monszpart, N. Mellado, G. J. Brostow, and N. J. Mitra · 2015
Later among the works it cites.
Completing 3D object shape from one depth image
J. Rock, T. Gupta, J. Thorsen, J. Gwak, D. Shin, and D. Hoiem · 2015
Later among the works it cites.
3D ShapeNets: A deep representation for volumetric shapes
Z. Wu, S. Song, A. Khosla, F. Yu, L. Zhang, X. Tang, and J. Xiao · 2015
Later among the works it cites.
Structured prediction of unobserved voxels from a single depth image
M. Firman, O. Mac Aodha, S. Julier, and G. J. Brostow · 2016
Closest in time.
Playing for data: Ground truth from computer games
S. R. Richter, V. Vineet, S. Roth, and V. Koltun · 2016
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A. X. Chang, T. Funkhouser, L. Guibas, P. Hanrahan, Q. Huang, Z. Li, S. Savarese, M. Savva, S. Song, H. Su, J. Xiao, L. Yi, and F. Yu · 2015
Cited alongside, same era.
Joint 3D object and layout inference from a single RGB-D image
A. Geiger and C. Wang · 2015
Cited alongside, same era.
Predicting complete 3D models of indoor scenes
R. Guo, C. Zou, and D. Hoiem · 2015
Cited alongside, same era.
Aligning 3D models to RGB-D images of cluttered scenes
S. Gupta, P. A. Arbeláez, R. B. Girshick, and J. Malik · 2015
Cited alongside, same era.
SceneNet: Understanding real world indoor scenes with synthetic data
A. Handa, V. Patraucean, V. Badrinarayanan, S. Stent, and R. Cipolla · 2015
Cited alongside, same era.
Object detection and classification from large-scale cluttered indoor scans
Y. Li, A. Dai, L. Guibas, and M. Nießner · 2015
Cited alongside, same era.
Large-scale semantic 3d reconstruction: an adaptive multi-resolution model for multi-class volumetric labeling
M. Bláha, C. Vogel, A. Richard, J. D. Wegner, T. Pock, and K. Schindler
Cited in the paper.
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Deep sliding shapes for amodal 3D object detection in rgb-d images
S. Song and J. Xiao · 2016
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A field model for repairing 3D shapes
D. Thanh Nguyen, B.-S. Hua, K. Tran, Q.-H. Pham, and S.-K. Yeung · 2016
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Shape completion enabled robotic grasping
J. Varley, C. DeChant, A. Richardson, A. Nair, J. Ruales, and P. Allen · 2016
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Multi-scale context aggregation by dilated convolutions
F. Yu and V. Koltun · 2016
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3DMatch: Learning the matching of local 3D geometry in range scans
A. Zeng, S. Song, M. Nießner, M. Fisher, and J. Xiao · 2016
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