Fetching the paper…
Reading the bibliography…
There have been remarkable improvements in the semantic labelling task in the recent years.
Conditional random fields: probabilistic models for segmenting and labeling sequence data
J. D. Lafferty, A. McCallum, and F. C. N. Pereira · 2001
Earlier work this paper cites.
ImageNet: A Large-Scale Hierarchical Image Database
J. Deng, W. Dong, R. Socher, L.-J. Li, K. Li, and L. Fei-Fei · 2009
Earlier work this paper cites.
Can saliency map models predict human egocentric visual attention?
K. Yamada, Y. Sugano, T. Okabe, Y. Sato, A. Sugimoto, and K. Hiraki · 2010
Earlier work this paper cites.
Semantic contours from inverse detectors
B. Hariharan, P. Arbeláez, L. Bourdev, S. Maji, and J. Malik · 2011
Earlier work this paper cites.
Efficient inference in fully connected crfs with gaussian edge potentials
P. Krähenbühl and V. Koltun · 2011
Earlier work this paper cites.
Learning to detect a salient object
T. Liu, Z. Yuan, J. Sun, J. Wang, N. Zheng, X. Tang, and H.-Y. Shum · 2011
Earlier work this paper cites.
Weakly supervised semantic segmentation with a multi-image model
A. Vezhnevets, V. Ferrari, and J. Buhmann · 2011
Earlier work this paper cites.
The PASCAL Visual Object Classes Challenge 2012 (VOC2012) Results
M. Everingham, L. Van Gool, C. K. I. Williams, J. Winn, and A. Zisserman · 2012
Earlier work this paper cites.
Salient object detection: A discriminative regional feature integration approach
H. Jiang, J. Wang, Z. Yuan, Y. Wu, N. Zheng, and S. Li · 2013
Earlier work this paper cites.
What makes a patch distinct?
R. Margolin, A. Tal, and L. Zelnik-Manor · 2013
Earlier work this paper cites.
The secrets of salient object segmentation
Y. Li, X. Hou, C. Koch, J. M. Rehg, and A. L. Yuille · 2014
Earlier work this paper cites.
Microsoft coco: Common objects in context
T. Lin, M. Maire, S. Belongie, J. Hays, P. Perona, D. Ramanan, P. Dollár, and C. L. Zitnick · 2014
Earlier work this paper cites.
Recurrent convolutional neural networks for scene labeling
P. O. Pinheiro and R. Collobert · 2014
Earlier work this paper cites.
Deep inside convolutional networks: Visualising image classification models and saliency maps
K. Simonyan, A. Vedaldi, and A. Zisserman · 2014
Earlier work this paper cites.
Visualizing and understanding convolutional networks
M. D. Zeiler and R. Fergus · 2014
Earlier work this paper cites.
Segnet: A deep convolutional encoder-decoder architecture for image segmentation
V. Badrinarayanan, A. Kendall, and R. Cipolla · 2015
Earlier work this paper cites.
What’s the point: Semantic segmentation with point supervision
A. Bearman, O. Russakovsky, V. Ferrari, and L. Fei-Fei · 2015
Earlier work this paper cites.
Salient object detection: A benchmark
A. Borji, M.-M. Cheng, H. Jiang, and J. Li · 2015
Earlier work this paper cites.
Look and think twice: Capturing top-down visual attention with feedback convolutional neural networks
C. Cao, X. Liu, Y. Yang, Y. Yu, J. Wang, Z. Wang, Y. Huang, L. Wang, C. Huang, W. Xu, D. Ramanan, and T. Huang · 2015
Cited alongside, same era.
Global contrast based salient region detection
M.-M. Cheng, N. J. Mitra, X. Huang, P. H. S. Torr, and S.-M. Hu · 2015
Cited alongside, same era.
Boxsup: Exploiting bounding boxes to supervise convolutional networks for semantic segmentation
J. Dai, K. He, and J. Sun · 2015
Cited alongside, same era.
Fully convolutional networks for semantic segmentation
J. Long, E. Shelhamer, and T. Darrell · 2015
Cited alongside, same era.
Learning deconvolution network for semantic segmentation
H. Noh, S. Hong, and B. Han · 2015
Cited alongside, same era.
Weakly- and semi-supervised learning of a dcnn for semantic image segmentation
L.-C. Chen, G. Papandreou, I. Kokkinos, K. Murphy, and A. L. Yuille · 2016
Later among the works it cites.
Deep residual learning for image recognition
K. He, X. Zhang, S. Ren, and J. Sun · 2016
Later among the works it cites.
Contextlocnet: Context-aware deep network models for weakly supervised localization
V. Kantorov, M. Oquab, M. Cho, and I. Laptev · 2016
Later among the works it cites.
Weakly supervised semantic labelling and instance segmentation
A. Khoreva, R. Benenson, J. Hosang, M. Hein, and B. Schiele · 2016
Later among the works it cites.
Improving weakly-supervised object localization by micro-annotation
A. Kolesnikov and C. Lampert · 2016
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
G. Papandreou, L. Chen, K. Murphy, , and A. L. Yuille · 2015
Cited alongside, same era.
Constrained convolutional neural networks for weakly supervised segmentation
D. Pathak, P. Kraehenbuehl, and T. Darrell · 2015
Cited alongside, same era.
Fully convolutional multi-class multiple instance learning
D. Pathak, E. Shelhamer, J. Long, and T. Darrell · 2015
Cited alongside, same era.
From image-level to pixel-level labeling with convolutional network
P. Pinheiro and R. Collobert · 2015
Cited alongside, same era.
Multiscale combinatorial grouping for image segmentation and object proposal generation
J. Pont-Tuset, P. Arbeláez, J. Barron, F. Marques, and J. Malik · 2015
Cited alongside, same era.
Very deep convolutional networks for large-scale image recognition
K. Simonyan and A. Zisserman · 2015
Cited alongside, same era.
Striving for simplicity: The all convolutional net
J. Springenberg, A. Dosovitskiy, T. Brox, and M. Riedmiller · 2015
Cited alongside, same era.
Seed, expand and constrain: Three principles for weakly-supervised image segmentation
A. Kolesnikov and C. H. Lampert · 2016
Later among the works it cites.
Deep contrast learning for salient object detection
G. Li and Y. Yu · 2016
Later among the works it cites.
Deepsaliency: Multi-task deep neural network model for salient object detection
X. Li, L. Zhao, L. Wei, M. H. Yang, F. Wu, Y. Zhuang, H. Ling, and J. Wang · 2016
Later among the works it cites.
Scribblesup: Scribble-supervised convolutional networks for semantic segmentation
D. Lin, J. Dai, J. Jia, K. He, and J. Sun · 2016
Later among the works it cites.
Augmented feedback in semantic segmentation under image level supervision
X. Qi, Z. Liu, J. Shi, H. Zhao, and J. Jia · 2016
Later among the works it cites.
Built-in foreground/background prior for weakly-supervised semantic segmentation
F. Saleh, M. S. A. Akbarian, M. Salzmann, L. Petersson, S. Gould, and J. M. Alvarez · 2016
Later among the works it cites.
Convexification of learning from constraints
I. Shcherbatyi and B. Andres · 2016
Later among the works it cites.
Hierarchical image saliency detection on extended cssd
J. Shi, Q. Yan, L. Xu, and J. Jia · 2016
Later among the works it cites.
Distinct class-specific saliency maps for weakly supervised semantic segmentation
W. Shimoda and K. Yanai · 2016
Later among the works it cites.
Attention networks for weakly supervised object localization
E. Teh, M. Rochan, and Y. Wang · 2016
Later among the works it cites.
Multi-scale context aggregation by dilated convolutions
F. Yu and V. Koltun · 2016
Later among the works it cites.
Top-down neural attention by excitation backprop
J. Zhang, Z. Lin, J. Brandt, X. Shen, and S. Sclaroff · 2016
Later among the works it cites.
Learning Deep Features for Discriminative Localization
B. Zhou, A. Khosla, L. A., A. Oliva, and A. Torralba · 2016
Later among the works it cites.