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This paper introduces a deep architecture for segmenting 3D objects into their labeled semantic parts.
Illumination for computer generated pictures
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Class-specific grasping of 3D objects from a single 2D image
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Learning 3D mesh segmentation and labeling
E. Kalogerakis, A. Hertzmann, and K. Singh · 2010
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Contextual part analogies in 3D objects
L. Shapira, S. Shalom, A. Shamir, D. Cohen-Or, and H. Zhang · 2010
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Probabilistic reasoning for assembly-based 3D modeling
S. Chaudhuri, E. Kalogerakis, L. Guibas, and V. Koltun · 2011
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Joint shape segmentation with linear programming
Q. Huang, V. Koltun, and L. Guibas · 2011
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A large-scale hierarchical multi-view RGB-D object dataset
K. Lai, L. Bo, X. Ren, and D. Fox · 2011
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Real-time human pose recognition in parts from a single depth image
J. Shotton, A. Fitzgibbon, A. Blake, A. Kipman, M. Finocchio, R. Moore, and T. Sharp · 2011
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Unsupervised co-segmentation of a set of shapes via descriptor-space spectral clustering
O. Sidi, O. van Kaick, Y. Kleiman, H. Zhang, and D. Cohen-Or · 2011
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Prior knowledge for part correspondence
O. van Kaick, A. Tagliasacchi, O. Sidi, H. Zhang, D. Cohen-Or, L. Wolf, and G. Hamarneh · 2011
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A learned feature descriptor for object recognition in RGB-D data
M. Blum, J. T. Springenberg, J. Wülfing, and M. Riedmiller · 2012
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3D object detection and viewpoint estimation with a deformable 3D cuboid model
S. Fidler, S. Dickinson, and R. Urtasun · 2012
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Co-segmentation of 3D shapes via subspace clustering
R. Hu, L. Fan, and L. Liu · 2012
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A probabilistic model for component-based shape synthesis
E. Kalogerakis, S. Chaudhuri, D. Koller, and V. Koltun · 2012
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Active co-analysis of a set of shapes
Y. Wang, S. Asafi, O. van Kaick, H. Zhang, D. Cohen-Or, and B. Chen · 2012
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Example-based 3D object reconstruction from line drawings
T. Xue, J. Liu, and X. Tang · 2012
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Unsupervised feature learning for RGB-D based object recognition
L. Bo, X. Ren, and D. Fox · 2013
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AttribIt: Content creation with semantic attributes
S. Chaudhuri, E. Kalogerakis, S. Giguere, , and T. Funkhouser · 2013
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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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Learning part-based templates from large collections of 3D shapes
V. G. Kim, W. Li, N. J. Mitra, S. Chaudhuri, S. DiVerdi, and T. Funkhouser · 2013
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Semantic 3D Object Maps for Everyday Robot Manipulation
R. B. Rusu · 2013
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Regularization of neural networks using DropConnect
L. Wan, M. Zeiler, S. Zhang, Y. LeCun, and R. Fergus · 2013
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Projective analysis for 3D shape segmentation
Y. Wang, M. Gong, T. Wang, D. Cohen-Or, H. Zhang, and B. Chen · 2013
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Feedforward semantic segmentation with zoom-out features
M. Mostajabi, P. Yadollahpour, and G. Shakhnarovich · 2015
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Learning deconvolution network for semantic segmentation
H. Noh, S. Hong, and B. Han · 2015
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Multi-view and 3D deformable part models
B. Pepik, M. Stark, P. Gehler, and B. Schiele · 2015
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Very deep convolutional networks for large-scale image recognition
K. Simonyan and A. Zisserman · 2015
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SUN RGB-D: A RGB-D scene understanding benchmark suite
S. Song, S. P. Lichtenberg, and J. Xiao · 2015
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Deep sliding shapes for amodal 3D object detection in RGB-D images
S. Song and J. Xiao · 2015
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Learning rich features from RGB-D images for object detection and segmentation
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Simultaneous detection and segmentation
B. Hariharan, P. Arbeláez, R. Girshick, and J. Malik · 2014
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Functional map networks for analyzing and exploring large shape collections
Q. Huang, F. Wang, and L. Guibas · 2014
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FPM: Fine pose parts-based model with 3D cad models
J. J. Lim, A. Khosla, and A. Torralba · 2014
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Co-segmentation of textured 3D shapes with sparse annotations
M. E. Yumer, W. Chun, and A. Makadia · 2014
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Shapenet: An information-rich 3d model repository
A. X. Chang, T. A. Funkhouser, L. J. Guibas, P. Hanrahan, Q.-X. Huang, Z. Li, S. Savarese, M. Savva, S. Song, H. Su, J. Xiao, L. Yi, and F. Yu · 2015
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Multi-view convolutional neural networks for 3D shape recognition
H. Su, S. Maji, E. Kalogerakis, and E. Learned-Miller · 2015
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Projective feature learning for 3D shapes with multi-view depth images
Z. Xie, K. Xu, W. Shan, L. Liu, Y. Xiong, and H. Huang · 2015
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Conditional random fields as recurrent neural networks
S. Zheng, S. Jayasumana, B. Romera-Paredes, V. Vineet, Z. Su, D. Du, C. Huang, and P. H. Torr · 2015
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A large dataset of object scans
S. Choi, Q.-Y. Zhou, S. Miller, and V. Koltun · 2016
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Fusenet: Incorporating depth into semantic segmentation via fusion-based CNN architecture
C. Hazirbas, L. Ma, C. Domokos, and D. Cremers · 2016
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Shape synthesis from sketches via procedural models and convolutional networks
H. Huang, E. Kalogerakis, E. Yumer, and R. Měch · 2016
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Functionality preserving shape style transfer
Z. Lun, E. Kalogerakis, R. Wang, and A. Sheffer · 2016
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Volumetric and multi-view CNNs for object classification on 3D data
C. R. Qi, H. Su, M. Niessner, A. Dai, M. Yan, and L. J. Guibas · 2016
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Unsupervised learning of 3D structure from images
D. J. Rezende, S. M. A. Eslami, S. Mohamed, P. Battaglia, M. Jaderberg, and N. Heess · 2016
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Data-driven shape analysis and processing
K. Xu, V. G. Kim, Q. Huang, and E. Kalogerakis · 2016
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Perspective transformer nets: Learning single-view 3D object reconstruction without 3D supervision
X. Yan, J. Yang, E. Yumer, Y. Guo, and H. Lee · 2016
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A scalable active framework for region annotation in 3D shape collections
L. Yi, V. G. Kim, D. Ceylan, I.-C. Shen, M. Yan, H. Su, C. Lu, Q. Huang, A. Sheffer, and L. Guibas · 2016
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Multi-scale context aggregation by dilated convolutions
F. Yu and V. Koltun · 2016
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Learning dense correspondence via 3D-guided cycle consistency
T. Zhou, P. Krähenbühl, M. Aubry, Q. Huang, and A. A. Efros · 2016
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