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We study the notion of consistency between a 3D shape and a 2D observation and propose a differentiable formulation which allows computing gradients of the 3D shape given an observation from an arbitrary view.
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Reconstructing pascal voc
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ShapeNet: An Information-Rich 3D Model Repository
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Predicting depth, surface normals and semantic labels with a common multi-scale convolutional architecture
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Single image 3D without a single 3D image
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Hypercolumns for object segmentation and fine-grained localization
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Imagenet large scale visual recognition challenge
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Deep residual learning for image recognition
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Unsupervised learning of 3d structure from images
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Learning category-specific deformable 3d models for object reconstruction
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Single image 3d interpreter network
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Discrete optimization of ray potentials for semantic 3d reconstruction
N. Savinov, C. Häne, M. Pollefeys, et al · 2015
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Render for cnn: Viewpoint estimation in images using cnns trained with rendered 3d model views
H. Su, C. R. Qi, Y. Li, and L. J. Guibas · 2015
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Viewpoints and keypoints
S. Tulsiani and J. Malik · 2015
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Towards probabilistic volumetric reconstruction using ray potentials
A. O. Ulusoy, A. Geiger, and M. J. Black · 2015
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3d-r2n2: A unified approach for single and multi-view 3d object reconstruction
C. B. Choy, D. Xu, J. Gwak, K. Chen, and S. Savarese · 2016
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The cityscapes dataset for semantic urban scene understanding
M. Cordts, M. Omran, S. Ramos, T. Rehfeld, M. Enzweiler, R. Benenson, U. Franke, S. Roth, and B. Schiele · 2016
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Unsupervised cnn for single view depth estimation: Geometry to the rescue
R. Garg and I. Reid · 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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Multi-scale context aggregation by dilated convolutions
F. Yu and V. Koltun · 2016
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Unsupervised monocular depth estimation with left-right consistency
C. Godard, O. Mac Aodha, and G. J. Brostow · 2017
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Hierarchical surface prediction for 3d object reconstruction
C. Häne, S. Tulsiani, and J. Malik · 2017
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Octnetfusion: Learning depth fusion from data
G. Riegler, A. O. Ulusoy, H. Bischof, and A. Geiger · 2017
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Octree generating networks: Efficient convolutional architectures for high-resolution 3d outputs
M. Tatarchenko, A. Dosovitskiy, and T. Brox · 2017
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Unsupervised learning of depth and ego-motion from video
T. Zhou, M. Brown, N. Snavely, and D. Lowe · 2017
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