Fetching the paper…
Reading the bibliography…
Most approaches for instance-aware semantic labeling traditionally focus on accuracy.
The estimation of the gradient of a density function, with applications in pattern recognition
Keinosuke Fukunaga and Larry Hostetler · 1975
Earlier work this paper cites.
A robust hybrid of lasso and ridge regression
Art B Owen · 2007
Earlier work this paper cites.
Distance metric learning for large margin nearest neighbor classification
Kilian Q Weinberger and Lawrence K Saul · 2009
Earlier work this paper cites.
Imagenet classification with deep convolutional neural networks
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton · 2012
Earlier work this paper cites.
Depth map prediction from a single image using a multi-scale deep network
David Eigen, Christian Puhrsch, and Rob Fergus · 2014
Earlier work this paper cites.
Rich feature hierarchies for accurate object detection and semantic segmentation
Ross Girshick, Jeff Donahue, Trevor Darrell, and Jitendra Malik · 2014
Earlier work this paper cites.
Simultaneous detection and segmentation
Bharath Hariharan, Pablo Arbeláez, Ross Girshick, and Jitendra Malik · 2014
Earlier work this paper cites.
Very deep convolutional networks for large-scale image recognition
Karen Simonyan and Andrew Zisserman · 2014
Earlier work this paper cites.
Segnet: A deep convolutional encoder-decoder architecture for image segmentation
Vijay Badrinarayanan, Alex Kendall, and Roberto Cipolla · 2015
Cited alongside, same era.
Predicting depth, surface normals and semantic labels with a common multi-scale convolutional architecture
David Eigen and Rob Fergus · 2015
Cited alongside, same era.
Fully convolutional networks for semantic segmentation
Jonathan Long, Evan Shelhamer, and Trevor Darrell · 2015
Cited alongside, same era.
Deep watershed transform for instance segmentation
Min Bai and Raquel Urtasun · 2016
Cited alongside, same era.
Shape-aware instance segmentation
Zeeshan Hayder, Xuming He, and Mathieu Salzmann · 2016
Cited alongside, same era.
Deeper depth prediction with fully convolutional residual networks
Iro Laina, Christian Rupprecht, Vasileios Belagiannis, Federico Tombari, and Nassir Navab · 2016
Later among the works it cites.
Enet: A deep neural network architecture for real-time semantic segmentation
Adam Paszke, Abhishek Chaurasia, Sangpil Kim, and Eugenio Culurciello · 2016
Later among the works it cites.
Multinet: Real-time joint semantic reasoning for autonomous driving
Marvin Teichmann, Michael Weber, Marius Zoellner, Roberto Cipolla, and Raquel Urtasun · 2016
Later among the works it cites.
Pixel-level encoding and depth layering for instance-level semantic labeling
Jonas Uhrig, Marius Cordts, Uwe Franke, and T. Brox · 2016
Later among the works it cites.
Pixelwise instance segmentation with a dynamically instantiated network
Anurag Arnab and Philip H. S. Torr · 2017
Closest in time.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Instancecut: from edges to instances with multicut
Alexander Kirillov, Evgeny Levinkov, Bjoern Andres, Bogdan Savchynskyy, and Carsten Rother · 2016
Cited alongside, same era.
Iasonas Kokkinos · 2016
Cited alongside, same era.
Speeding up semantic segmentation for autonomous driving
Michael Treml, José Arjona-Medina, Thomas Unterthiner, Rupesh Durgesh, Felix Friedmann, Peter Schuberth, Andreas Mayr, Martin Heusel, Markus Hofmarcher, Michael Widrich, et al
Cited in the paper.
Semantic instance segmentation with a discriminative loss function
Bert De Brabandere, Davy Neven, and Luc Van Gool · 2017
Closest in time.
Kaiming He, Georgia Gkioxari, Piotr Dollár, and Ross Girshick · 2017
Closest in time.