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This paper aims at developing a faster and a more accurate solution to the amodal 3D object detection problem for indoor scenes.
The pascal visual object classes (voc) challenge
M. Everingham, L. V. Gool, C. K. Williams, J. Winn, and A. Zisserman · 2010
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Object detection with discriminatively trained part-based models
P. Felzenszwalb, R. Girshick, D. McAllester, and D. Ramanan · 2010
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Cpmc: Automatic object segmentation using constrained parametric min-cuts
J. Carreira and C. Sminchisescu · 2012
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Indoor segmentation and support inference from rgbd images
S. Nathan, H. Derek, K. Pushmeet, and R. Fergus · 2012
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Accurate localization of 3d object from rgb-d data using segmentation hypothesis
B. soo Kim, S. Xu, and S. Savarese · 2013
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Holistic scene understanding for 3d object detection with rgbd cameras
B. soo Kim, S. Xu, and S. Savarese · 2013
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Multiscale combinatorial grouping
P. Arbelaez, J. Pont-Tuset, J. T. Barron, F. Marques, and J. Malik · 2014
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Rich feature hierarchies for accurate object detection and segmentation
R. Girshick, J. Donahue, T. Darrell, and J. Malik · 2014
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Learning rich features from rgb-d images for object detection and segmentation
S. Gupta, R. Girshick, P. Arbelaez, and J. Malik · 2014
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Microsoft coco: Com- mon objects in context
T.-Y. Lin, M. Maire, S. Belongie, J. Hays, P. Perona, D. Ramanan, P. Dolĺar, and C. L. Zitnick · 2014
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Sliding shapes for 3d object detection in depth images
S. Song and J. Xiao · 2014
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Fast r-cnn
R. Girshick · 2015
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Aligning 3d models to rgb-d images of cluttered scenes
S. Gupta, P. Arbelaez, R. Girshick, and J. Malik · 2015
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Towards 3d object detection with bimodal deep boltzmann machines over rgbd imagery
W. Liu, R. Ji, and S. Li · 2015
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Faster r-cnn: Towards real-time object detection with region proposal networks
S. Ren, K. He, R. Girshick, and J. Sun · 2015
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Imagenet large scale visual recognition challenge
O. Russakovsky, J. Deng, H. Su, J. Krause, S. Satheesh, S. Ma, Z. Huang, A. Karpathy, A. Khosla, M. Bernstein, and et al · 2015
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Three-dimensional object detection and layout prediction using clouds of oriented gradients
Z. Ren and E. B. Sudderth · 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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Multi-view 3d object detection network for autonomous driving
X. Chen, H. Ma, J. Wan, B. Li, and T. Xia · 2017
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Amodal detection of 3d objects: Inferring 3d bounding boxed from 2d ones in rgb-depth images
Z. Deng and L. J. Latecki · 2017
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Mask r-cnn
K. He, G. Gkioxari, P. Dollár, and R. Girshick · 2017
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2d-driven 3d object detection in rgb-d images
J. Lahoud and B. Ghanem · 2017
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Feature pyramid networks for object detection
T.-Y. Lin, P. Dollar, R. Girshick, K. He, B. Hariharan, and S. Belongie · 2017
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Focal loss for dense object detection
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