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The problem of computing category agnostic bounding box proposals is utilized as a core component in many computer vision tasks and thus has lately attracted a lot of attention.
The pascal visual object classes (voc) challenge
Mark Everingham, Luc Van Gool, Christopher KI Williams, John Winn, and Andrew Zisserman · 2010
Earlier work this paper cites.
Object detection with discriminatively trained part-based models
Pedro F Felzenszwalb, Ross B Girshick, David McAllester, and Deva Ramanan · 2010
Earlier work this paper cites.
Edge boxes: Locating object proposals from edges
C Lawrence Zitnick and Piotr Dollár · 2010
Earlier work this paper cites.
Segmentation as selective search for object recognition
Koen EA Van de Sande, Jasper RR Uijlings, Theo Gevers, and Arnold WM Smeulders · 2011
Earlier work this paper cites.
Measuring the objectness of image windows
Bogdan Alexe, Thomas Deselaers, and Vittorio Ferrari · 2012
Earlier work this paper cites.
Indoor segmentation and support inference from rgbd images
Pushmeet Kohli Nathan Silberman, Derek Hoiem and Rob Fergus · 2012
Earlier work this paper cites.
Overfeat: Integrated recognition, localization and detection using convolutional networks
Pierre Sermanet, David Eigen, Xiang Zhang, Michaël Mathieu, Rob Fergus, and Yann LeCun · 2013
Earlier work this paper cites.
Multiscale combinatorial grouping
P. Arbeláez, J. Pont-Tuset, J. Barron, F. Marques, and J. Malik · 2014
Earlier work this paper cites.
Bing: Binarized normed gradients for objectness estimation at 300fps
Ming-Ming Cheng, Ziming Zhang, Wen-Yan Lin, and Philip Torr · 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.
How good are detection proposals, really?
J. Hosang, R. Benenson, and B. Schiele · 2014
Earlier work this paper cites.
Geodesic object proposals
Philipp Krähenbühl and Vladlen Koltun · 2014
Earlier work this paper cites.
Microsoft coco: Common objects in context
Tsung-Yi Lin, Michael Maire, Serge Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C Lawrence Zitnick · 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.
Cracking bing and beyond
Qiyang Zhao, Zhibin Liu, and Baolin Yin · 2014
Cited alongside, same era.
Inside-outside net: Detecting objects in context with skip pooling and recurrent neural networks
Sean Bell, C Lawrence Zitnick, Kavita Bala, and Ross Girshick · 2015
Cited alongside, same era.
Object-proposal evaluation protocol is’ gameable’
Neelima Chavali, Harsh Agrawal, Aroma Mahendru, and Dhruv Batra · 2015
Cited alongside, same era.
Improving object proposals with multi-thresholding straddling expansion
Xiaozhi Chen, Huimin Ma, Xiang Wang, and Zhichen Zhao · 2015
Cited alongside, same era.
Weakly supervised object localization with multi-fold multiple instance learning
Ramazan Gokberk Cinbis, Jakob Verbeek, and Cordelia Schmid · 2015
Cited alongside, same era.
Deepbox: Learning objectness with convolutional networks
Weicheng Kuo, Bharath Hariharan, and Jitendra Malik · 2015
Later among the works it cites.
Learning to segment object candidates
Pedro O Pinheiro, Ronan Collobert, and Piotr Dollar · 2015
Later among the works it cites.
Faster r-cnn: Towards real-time object detection with region proposal networks
Shaoqing Ren, Kaiming He, Ross Girshick, and Jian Sun · 2015
Later among the works it cites.
Imagenet large scale visual recognition challenge
Olga Russakovsky, Jia Deng, Hao Su, Jonathan Krause, Sanjeev Satheesh, Sean Ma, Zhiheng Huang, Andrej Karpathy, Aditya Khosla, Michael Bernstein, et al · 2015
Later among the works it cites.
Where to look: Focus regions for visual question answering
Kevin J Shih, Saurabh Singh, and Derek Hoiem · 2015
Later among the works it cites.
Locnet: Improving localization accuracy for object detection
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Instance-aware semantic segmentation via multi-task network cascades
Jifeng Dai, Kaiming He, and Jian Sun · 2015
Cited alongside, same era.
Deepproposal: Hunting objects by cascading deep convolutional layers
Amir Ghodrati, Ali Diba, Marco Pedersoli, Tinne Tuytelaars, and Luc Van Gool · 2015
Cited alongside, same era.
Object detection via a multi-region & semantic segmentation-aware cnn model
Spyros Gidaris and Nikos Komodakis · 2015
Cited alongside, same era.
Fast r-cnn
Ross Girshick · 2015
Cited alongside, same era.
Saurabh Gupta and Jitendra Malik · 2015
Cited alongside, same era.
What makes for effective detection proposals?
Jan Hosang, Rodrigo Benenson, Piotr Dollár, and Bernt Schiele · 2015
Cited alongside, same era.
Deep visual-semantic alignments for generating image descriptions
Andrej Karpathy and Li Fei-Fei · 2015
Cited alongside, same era.
Spyros Gidaris and Nikos Komodakis · 2016
Closest in time.
Learning to co-generate object proposals with a deep structured network
Zeeshan Hayder, Xuming He, and Mathieu Salzmann · 2016
Closest in time.
Densecap: Fully convolutional localization networks for dense captioning
Justin Johnson, Andrej Karpathy, and Li Fei-Fei · 2016
Closest in time.
Deep exemplar 2d-3d detection by adapting from real to rendered views
Francisco Massa, Bryan Russell, and Mathieu Aubry · 2016
Closest in time.
Learning to refine object segments
Pedro H. O. Pinheiro, Tsung-Yi Lin, Ronan Collobert, and Piotr Dollár · 2016
Closest in time.
Training region-based object detectors with online hard example mining
Abhinav Shrivastava, Abhinav Gupta, and Ross Girshick · 2016
Closest in time.
Sergey Zagoruyko and Nikos Komodakis · 2016
Closest in time.
A multipath network for object detection
Sergey Zagoruyko, Adam Lerer, Tsung-Yi Lin, Pedro O Pinheiro, Sam Gross, Soumith Chintala, and Piotr Dollár · 2016
Closest in time.