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Deep learning requires large amounts of training data to be effective.
Interactive graph cuts for optimal boundary & region segmentation of objects in n-d images
Y. Y. Boykov and M-P. Jolly · 2001
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GrabCut - interactive foreground extraction using iterated graph cuts
C. Rother, V. Kolmogorov, and A. Blake · 2004
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Random walks for image segmentation
L. Grady · 2006
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A geodesic framework for fast interactive image and video segmentation and matting
X. Bai and G. Sapiro · 2007
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Imagenet: A large-scale hierarchical image database
J. Deng, W. Dong, R. Socher, L. J. Li, Kai Li, and Li Fei-Fei · 2009
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The pascal visual object classes (VOC) challenge
M. Everingham, L. Van Gool, C. K. I. Williams, J. Winn, and A. Zisserman · 2010
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Semantic contours from inverse detectors
B. Hariharan, P. Arbelaez, L. Bourdev, S. Maji, and J. Malik · 2011
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Are we ready for autonomous driving? the kitti vision benchmark suite
A. Geiger, P. Lenz, and R. Urtasun · 2012
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Beat the MTurkers: Automatic image labeling from weak 3d supervision
L-C. Chen, S. Fidler, and R. Urtasun · 2014
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Microsoft COCO: Common objects in context
T-Y. Lin, M. Maire, S. Belongie, J. Hays, P. Perona, D. Ramanan, P. Dollár, and C. L. Zitnick · 2014
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Adam: A method for stochastic optimization
D. P. Kingma and J. Ba · 2015
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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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Scribblesup: Scribble-supervised convolutional networks for semantic segmentation
D. Lin, J. Dai, J. Jia, K. He, and J. Sun · 2016
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A benchmark dataset and evaluation methodology for video object segmentation
F. Perazzi, J. Pont-Tuset, B. McWilliams, L. Van Gool, M. Gross, and A. Sorkine-Hornung · 2016
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Learning to refine object segments
P.H.O. Pinheiro, T.-Y. Lin, R. Collobert, and P. Dollár · 2016
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Bridging category-level and instance-level semantic image segmentation
Z. Wu, C. Shen, and A. van den Hengel · 2016
Rethinking atrous convolution for semantic image segmentation
L-C. Chen, G. Papandreou, F. Schroff, and H. Adam · 2017
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Lucid data dreaming for object tracking
A. Khoreva, R. Benenson, E. Ilg, T. Brox, and B. Schiele · 2017
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Regional interactive image segmentation networks
J.H. Liew, Y. Wei, W. Xiong, S-H. Ong, and J. Feng · 2017
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Deep extreme cut: From extreme points to object segmentation
K-K. Maninis, S. Caelles, J. Pont-Tuset, and L. Van Gool · 2017
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Learning video object segmentation from static images
F. Perazzi, A. Khoreva, R. Benenson, B. Schiele, and A. Sorkine-Hornung · 2017
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Full-resolution residual networks for semantic segmentation in street scenes
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Deep interactive object selection
N. Xu, B. L. Price, S. Cohen, J. Yang, and T. S. Huang · 2016
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Loosecut: Interactive image segmentation with loosely bounded boxes
H. Yu, Y. Zhou, H. Qian, M. Xian, and S. Wang · 2016
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One-shot video object segmentation
S. Caelles, K.-K. Maninis, J. Pont-Tuset, L. Leal-Taixé, D. Cremers, and L. Van Gool · 2017
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Annotating object instances with a Polygon-RNN
L. Castrejón, K. Kundu, R. Urtasun, and S. Fidler · 2017
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T. Pohlen, A. Hermans, M. Mathias, and B. Leibe · 2017
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Online adaptation of convolutional neural networks for video object segmentation
P. Voigtlaender and B. Leibe · 2017
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Interactive video object segmentation in the wild
A. Benard and M. Gygli · 2018
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Encoder-decoder with atrous separable convolution for semantic image segmentation
L-C. Chen, Y. Zhu, G. Papandreou, F. Schroff, and H. Adam · 2018
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