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This work addresses the task of instance-aware semantic segmentation.
An efficient heuristic procedure for partitioning graphs
B. W. Kernighan and S. Lin · 1970
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A computational approach to edge detection
J. Canny · 1986
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Watersheds in digital spaces: an efficient algorithm based on immersion simulations
L. Vincent and P. Soille · 1991
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The partition problem
S. Chopra and M. R. Rao · 1993
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Long short-term memory
S. Hochreiter and J. Schmidhuber · 1997
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Normalized cuts and image segmentation
J. Shi and J. Malik · 2000
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Correlation clustering
N. Bansal, A. Blum, and S. Chawla · 2004
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The pascal visual object classes (voc) challenge
M. Everingham, L. Van Gool, C. K. Williams, J. Winn, and A. Zisserman · 2010
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Contour detection and hierarchical image segmentation
P. Arbelaez, M. Maire, C. Fowlkes, and J. Malik · 2011
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Contour detection and hierarchical image segmentation
P. Arbelaez, M. Maire, C. Fowlkes, and J. Malik · 2011
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Efficient inference in fully connected crfs with gaussian edge potentials
V. Koltun · 2011
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Sketch tokens: A learned mid-level representation for contour and object detection
J. J. Lim, C. L. Zitnick, and P. Dollár · 2013
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Multiscale combinatorial grouping
P. Arbeláez, J. Pont-Tuset, J. T. Barron, F. Marques, and J. Malik · 2014
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Cut, glue, & cut: A fast, approximate solver for multicut partitioning
T. Beier, T. Kroeger, J. H. Kappes, U. Köthe, and F. A. Hamprecht · 2014
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Simultaneous detection and segmentation
B. Hariharan, P. Arbeláez, R. Girshick, and J. Malik · 2014
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Crisp boundary detection using pointwise mutual information
P. Isola, D. Zoran, D. Krishnan, and E. H. Adelson · 2014
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Visual boundary prediction: A deep neural prediction network and quality dissection
J. J. Kivinen, C. K. Williams, N. Heess, and D. Technologies · 2014
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Asymmetric cuts: joint image labeling and partitioning
T. Kroeger, J. H. Kappes, T. Beier, U. Koethe, and F. A. Hamprecht · 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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Deepedge: A multi-scale bifurcated deep network for top-down contour detection
G. Bertasius, J. Shi, and L. Torresani · 2015
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High-for-low and low-for-high: Efficient boundary detection from deep object features and its applications to high-level vision
G. Bertasius, J. Shi, and L. Torresani · 2015
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Semantic segmentation with boundary neural fields
G. Bertasius, J. Shi, and L. Torresani · 2015
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Multi-instance object segmentation with occlusion handling
Y.-T. Chen, X. Liu, and M.-H. Yang · 2015
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Convolutional feature masking for joint object and stuff segmentation
J. Dai, K. He, and J. Sun · 2015
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Fully connected deep structured networks
A. G. Schwing and R. Urtasun · 2015
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Deepcontour: A deep convolutional feature learned by positive-sharing loss for contour detection
W. Shen, X. Wang, Y. Wang, X. Bai, and Z. Zhang · 2015
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Holistically-nested edge detection
S. Xie and Z. Tu · 2015
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Multi-scale context aggregation by dilated convolutions
F. Yu and V. Koltun · 2015
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Instance-level segmentation with deep densely connected mrfs
Z. Zhang, S. Fidler, and R. Urtasun · 2015
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J. Dai, K. He, and J. Sun · 2015
Cited alongside, same era.
Fast edge detection using structured forests
P. Dollár and C. L. Zitnick · 2015
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Hypercolumns for object segmentation and fine-grained localization
B. Hariharan, P. Arbeláez, R. Girshick, and J. Malik · 2015
Cited alongside, same era.
Pixel-wise deep learning for contour detection
J.-J. Hwang and T.-L. Liu · 2015
Cited alongside, same era.
A comparative study of modern inference techniques for structured discrete energy minimization problems
J. H. Kappes, B. Andres, F. A. Hamprecht, C. Schnörr, S. Nowozin, D. Batra, S. Kim, B. X. Kausler, T. Kröger, J. Lellmann, N. Komodakis, B. Savchynskyy, and C. Rother · 2015
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Efficient decomposition of image and mesh graphs by lifted multicuts
M. Keuper, E. Levinkov, N. Bonneel, G. Lavou, T. Brox, and B. Andres · 2015
Cited alongside, same era.
Reversible recursive instance-level object segmentation
X. Liang, Y. Wei, X. Shen, Z. Jie, J. Feng, L. Lin, and S. Yan · 2015
Cited alongside, same era.
Monocular object instance segmentation and depth ordering with cnns
Z. Zhang, A. G. Schwing, S. Fidler, and R. Urtasun · 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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L.-C. Chen, G. Papandreou, I. Kokkinos, K. Murphy, and A. L. Yuille · 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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Instance-sensitive fully convolutional networks
J. Dai, K. He, Y. Li, S. Ren, and J. Sun · 2016
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Laplacian pyramid reconstruction and refinement for semantic segmentation
G. Ghiasi and C. C. Fowlkes · 2016
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Joint graph decomposition and node labeling by local search
E. Levinkov, S. Tang, E. Insafutdinov, and B. Andres · 2016
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Multi-scale patch aggregation (MPA) for simultaneous detection and segmentation
S. Liu, X. Qi, J. Shi, H. Zhang, and J. Jia · 2016
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Learning to refine object segments
P. O. Pinheiro, T.-Y. Lin, R. Collobert, and P. Dollár · 2016
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End-to-end instance segmentation and counting with recurrent attention
M. Ren and R. S. Zemel · 2016
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Pixel-level encoding and depth layering for instance-level semantic labeling
J. Uhrig, M. Cordts, U. Franke, and T. Brox · 2016
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Bridging category-level and instance-level semantic image segmentation
Z. Wu, C. Shen, and A. v. d. Hengel · 2016
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A multipath network for object detection
S. Zagoruyko, A. Lerer, T.-Y. Lin, P. O. Pinheiro, S. Gross, S. Chintala, and P. Dollár · 2016
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