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Access to large, diverse RGB-D datasets is critical for training RGB-D scene understanding algorithms.
Poisson surface reconstruction
M. Kazhdan, M. Bolitho, and H. Hoppe · 2006
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Sun database: Large-scale scene recognition from abbey to zoo
J. Xiao, J. Hays, K. A. Ehinger, A. Oliva, and A. Torralba · 2010
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Interactive and anisotropic geometry processing using the screened poisson equation
M. Chuang and M. Kazhdan · 2011
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Indoor scene segmentation using a structured light sensor
N. Silberman and R. Fergus · 2011
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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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Recognizing scene viewpoint using panoramic place representation
J. Xiao, K. A. Ehinger, A. Oliva, and A. Torralba · 2012
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Data-driven 3D primitives for single image understanding
D. F. Fouhey, A. Gupta, and M. Hebert · 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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Holistic scene understanding for 3D object detection with rgbd cameras
D. Lin, S. Fidler, and R. Urtasun · 2013
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Real-time 3D reconstruction at scale using voxel hashing
M. Nießner, M. Zollhöfer, S. Izadi, and M. Stamminger · 2013
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Scene coordinate regression forests for camera relocalization in RGB-D images
J. Shotton, B. Glocker, C. Zach, S. Izadi, A. Criminisi, and A. Fitzgibbon · 2013
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Building part-based object detectors via 3D geometry
A. Shrivastava and A. Gupta · 2013
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SUN3D: A database of big spaces reconstructed using SFM and object labels
J. Xiao, A. Owens, and A. Torralba · 2013
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Estimating the 3D layout of indoor scenes and its clutter from depth sensors
J. Zhang, C. Kan, A. G. Schwing, and R. Urtasun · 2013
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Intrinsic images in the wild
S. Bell, K. Bala, and N. Snavely · 2014
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Unfolding an indoor origami world
D. F. Fouhey, A. Gupta, and M. Hebert · 2014
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Learning rich features from RGB-D images for object detection and segmentation: Supplementary material, 2014
S. Gupta, R. Girshick, P. Arbeláez, and J. Malik · 2014
Cited alongside, same era.
Sliding shapes for 3D object detection in depth images
S. Song and J. Xiao · 2014
Cited alongside, same era.
Learning deep features for scene recognition using places database
B. Zhou, A. Lapedriza, J. Xiao, A. Torralba, and A. Oliva · 2014
Cited alongside, same era.
Predicting depth, surface normals and semantic labels with a common multi-scale convolutional architecture
D. Eigen and R. Fergus · 2015
Cited alongside, same era.
Matchnet: Unifying feature and metric learning for patch-based matching
X. Han, T. Leung, Y. Jia, R. Sukthankar, and A. C. Berg · 2015
Cited alongside, same era.
SceneNet: Understanding real world indoor scenes with synthetic data
Deep unsupervised learning through spatial contrasting
E. Hoffer, I. Hubara, and N. Ailon · 2016
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SceneNN: A scene meshes dataset with annotations
B.-S. Hua, Q.-H. Pham, D. T. Nguyen, M.-K. Tran, L.-F. Yu, and S.-K. Yeung · 2016
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Deep reflectance maps
K. Rematas, T. Ritschel, M. Fritz, E. Gavves, and T. Tuytelaars · 2016
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PiGraphs: Learning Interaction Snapshots from Observations
M. Savva, A. X. Chang, P. Hanrahan, M. Fisher, and M. Nießner · 2016
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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. Handa, V. Patraucean, V. Badrinarayanan, S. Stent, and R. Cipolla · 2015
Cited alongside, same era.
Depth and surface normal estimation from monocular images using regression on deep features and hierarchical CRFs
B. Li, C. Shen, Y. Dai, A. van den Hengel, and M. He · 2015
Cited alongside, same era.
Discriminative learning of deep convolutional feature point descriptors
E. Simo-Serra, E. Trulls, L. Ferraz, I. Kokkinos, P. Fua, and F. Moreno-Noguer · 2015
Cited alongside, same era.
SUN RGB-D: A RGB-D scene understanding benchmark suite
S. Song, S. P. Lichtenberg, and J. Xiao · 2015
Cited alongside, same era.
SemanticPaint: Interactive 3D labeling and learning at your fingertips
J. Valentin, V. Vineet, M.-M. Cheng, D. Kim, J. Shotton, P. Kohli, M. Nießner, A. Criminisi, S. Izadi, and P. Torr · 2015
Cited alongside, same era.
Designing deep networks for surface normal estimation
X. Wang, D. Fouhey, and A. Gupta · 2015
Cited alongside, same era.
3D semantic parsing of large-scale indoor spaces
I. Armeni, O. Sener, A. R. Zamir, H. Jiang, I. Brilakis, M. Fischer, and S. Savarese · 2016
Cited alongside, same era.
S. Song, F. Yu, A. Zeng, A. X. Chang, M. Savva, and T. Funkhouser · 2016
Later among the works it cites.
Learning to navigate the energy landscape
J. Valentin, A. Dai, M. Nießner, P. Kohli, P. Torr, S. Izadi, and C. Keskin · 2016
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LIFT: Learned invariant feature transform
K. M. Yi, E. Trulls, V. Lepetit, and P. Fua · 2016
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Physically-based rendering for indoor scene understanding using convolutional neural networks
Y. Zhang, S. Song, E. Yumer, M. Savva, J.-Y. Lee, H. Jin, and T. Funkhouser · 2016
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Joint 2D-3D-semantic data for indoor scene understanding
I. Armeni, S. Sax, A. R. Zamir, and S. Savarese · 2017
Closest in time.
Scannet: Richly-annotated 3d reconstructions of indoor scenes
A. Dai, A. X. Chang, M. Savva, M. Halber, T. Funkhouser, and M. Nießner · 2017
Closest in time.
Bundlefusion: Real-time globally consistent 3d reconstruction using on-the-fly surface re-integration
A. Dai, M. Nießner, M. Zollöfer, S. Izadi, and C. Theobalt · 2017
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Structured global registration of rgb-d scans in indoor environments
M. Halber and T. Funkhouser · 2017
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Tanks and temples: Benchmarking large-scale scene reconstruction
A. Knapitsch, J. Park, Q.-Y. Zhou, and V. Koltun · 2017
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Self-supervised visual descriptor learning for dense correspondence
T. Schmidt, R. Newcombe, and D. Fox · 2017
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3DMatch: Learning local geometric descriptors from RGB-D reconstructions
A. Zeng, S. Song, M. Niessner, M. Fisher, J. Xiao, and T. Funkhouser · 2017
Closest in time.