Fetching the paper…
Reading the bibliography…
We propose 'Hide-and-Seek' a general purpose data augmentation technique, which is complementary to existing data augmentation techniques and is beneficial for various visual recognition tasks.
M. Weber, M. Welling, and P. Perona, “Unsupervised Learning of Models for Recognition,” in ECCV , 2000
2000
Earlier work this paper cites.
R. Fergus, P. Perona, and A. Zisserman, “Object Class Recognition by Unsupervised Scale-Invariant Learning,” in CVPR , 2003
2003
Earlier work this paper cites.
D. J. Crandall and D. P. Huttenlocher, “Weakly supervised learning of part-based spatial models for visual object recognition,” in ECCV , 2006
2006
Earlier work this paper cites.
P. Lucey, J. F. Cohn, T. Kanade, J. Saragih, Z. Ambadar, and I. Matthews, “The extended cohn-kanade dataset (ck+): A complete dataset for action unit and emotion-specified expression,” in CVPRW , 2010
2010
Earlier work this paper cites.
A. Krizhevsky, I. Sutskever, and G. Hinton, “Imagenet Classification with Deep Convolutional Neural Networks,” in NIPS , 2012
2012
Earlier work this paper cites.
P. Siva, C. Russell, and T. Xiang, “In Defence of Negative Mining for Annotating Weakly Labelled Data,” in ECCV , 2012
2012
Earlier work this paper cites.
K. Duan, D. Parikh, D. Crandall, and K. Grauman, “Discovering localized attributes for fine-grained recognition,” in CVPR , 2012
2012
Earlier work this paper cites.
A. Prest, C. Leistner, J. Civera, C. Schmid, and V. Ferrari, “Learning Object Class Detectors from Weakly Annotated Video,” in CVPR , 2012
2012
Earlier work this paper cites.
L. Wan, M. Zeiler, S. Zhang, Y. LeCun, and R. Fergus, “Regularization of neural network using dropconnect,” in ICML , 2013
2013
Earlier work this paper cites.
R. Girshick, J. Donahue, T. Darrell, and J. Malik, “Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation,” in CVPR , 2014
2014
Earlier work this paper cites.
H. Bilen, M. Pedersoli, and T. Tuytelaars, “Weakly supervised object detection with posterior regularization,” in BMVC , 2014
2014
Earlier work this paper cites.
C. Wang, W. Ren, K. Huang, and T. Tan, “Weakly supervised object localization with latent category learning,” in ECCV , 2014
2014
Earlier work this paper cites.
H. O. Song, Y. J. Lee, S. Jegelka, and T. Darrell, “Weakly-supervised discovery of visual pattern configurations,” in NIPS , 2014
2014
Earlier work this paper cites.
H. O. Song, R. Girshick, S. Jegelka, J. Mairal, Z. Harchaoui, and T. Darrell, “On Learning to Localize Objects with Minimal Supervision,” in ICML , 2014
2014
Earlier work this paper cites.
K. Simonyan, A. Vedaldi, and A. Zisserman, “Deep inside convolutional networks: Visualising image classification models and saliency maps,” in ICLR Workshop , 2014
2014
Earlier work this paper cites.
B. Hariharan, P. Arbeláez, R. Girshick, and J. Malik, “Simultaneous detection and segmentation,” in ECCV , 2014
2014
Earlier work this paper cites.
M. D. Zeiler and R. Fergus, “Visualizing and understanding convolutional networks,” in ECCV , 2014
2014
Earlier work this paper cites.
N. Srivastava, G. Hinton, A. Krizhevsky, I. Sutskever, and R. Salakhutdinov, “Dropout: A simple way to prevent neural networks from overfitting,” JMLR , 2014
2014
Earlier work this paper cites.
N. Zhang, M. Paluri, M. Ranzato, T. Darrell, and L. Bourdev, “PANDA: Pose Aligned Networks for Deep Attribute Modeling,” in CVPR , 2014
2014
Earlier work this paper cites.
M. Kiapour, K. Yamaguchi, A. C. Berg, and T. L. Berg, “Hipster wars: Discovering elements of fashion styles,” in ECCV , 2014
2014
Earlier work this paper cites.
R. Cinbis, J. Verbeek, and C. Schmid, “Multi-fold MIL Training for Weakly Supervised Object Localization,” in CVPR , 2014
2014
Earlier work this paper cites.
Y.-G. Jiang, J. Liu, A. Roshan Zamir, G. Toderici, I. Laptev, M. Shah, and R. Sukthankar, “THUMOS challenge: Action recognition with a large number of classes,” http://crcv.ucf.edu/THUMOS14/
2014
Cited alongside, same era.
A. Krizhevsky, V. Nair, and G. Hinton, “The cifar-10 dataset,” online: http://www. cs. toronto. edu/kriz/cifar. html , 2014
2014
Cited alongside, same era.
A. Karpathy, G. Toderici, S. Shetty, T. Leung, R. Sukthankar, and L. Fei-Fei, “Large-scale video classification with convolutional neural networks,” in CVPR , 2014
2014
Cited alongside, same era.
R. Girshick, “Fast r-cnn,” in ICCV , 2015
2015
Cited alongside, same era.
J. Long, E. Shelhamer, and T. Darrell, “Fully convolutional networks for semantic segmentation,” in CVPR , 2015
2015
Cited alongside, same era.
K. K. Singh, F. Xiao, and Y. J. Lee, “Track and transfer: Watching videos to simulate strong human supervision for weakly-supervised object detection,” in CVPR , 2016
2016
Later among the works it cites.
A. Khoreva, R. Benenson, M. Omran, M. Hein, and B. Schiele, “Weakly supervised object boundaries,” in CVPR , 2016
2016
Later among the works it cites.
S. Zagoruyko and N. Komodakis, “Wide residual networks,” BMVC , 2016
2016
Later among the works it cites.
L. Bazzani, B. A., D. Anguelov, and L. Torresani, “Self-taught object localization with deep networks,” in WACV , 2016
2016
Later among the works it cites.
D. Pathak, P. Krähenbühl, J. Donahue, T. Darrell, and A. Efros, “Context encoders: Feature learning by inpainting,” in CVPR , 2016
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…
2015
Cited alongside, same era.
M. Oquab, L. Bottou, I. Laptev, and J. Sivic, “Is object localization for free? – weakly-supervised learning with convolutional neural networks,” in CVPR , 2015
2015
Cited alongside, same era.
D. Pathak, P. Krähenbühl, and T. Darrell, “Constrained convolutional neural networks for weakly supervised segmentation,” in ICCV , 2015
2015
Cited alongside, same era.
C. Szegedy, W. Liu, Y. Jia, P. Sermanet, S. Reed, D. Anguelov, D. Erhan, V. Vanhoucke, and A. Rabinovich, “Going deeper with convolutions,” in CVPR , 2015
2015
Cited alongside, same era.
K. Simonyan and A. Zisserman, “Very deep convolutional networks for large-scale image recognition,” in ICLR , 2015
2015
Cited alongside, same era.
P. Khorrami, T. L. Paine, and T. S. Huang, “Do deep neural networks learn facial action units when doing expression recognition?” ICCV Workshop , 2015
2015
Cited alongside, same era.
J. Dai, K. He, and J. Sun, “Convolutional feature masking for joint object and stuff segmentation,” in CVPR , 2015
2015
Cited alongside, same era.
W. Liu, D. Anguelov, D. Erhan, C. Szegedy, S. Reed, C.-Y. Fu, and A. C. Berg, “Ssd: Single shot multibox detector,” in ECCV , 2016
2016
Later among the works it cites.
H. Bilen and A. Vedaldi, “Weakly supervised deep detection networks,” in CVPR , 2016
2016
Later among the works it cites.
V. Kantorov, M. Oquab, M. Cho, and I. Laptev, “Contextlocnet: Context-aware deep network models for weakly supervised localization,” in ECCV , 2016
2016
Later among the works it cites.
R. Rothe, R. Timofte, and L. V. Gool, “Deep expectation of real and apparent age from a single image without facial landmarks,” IJCV , 2016
2016
Later among the works it cites.
N. Liu and J. Han, “Dhsnet: Deep hierarchical saliency network for salient object detection,” in CVPR , 2016
2016
Later among the works it cites.
K. K. Singh and Y. J. Lee, “Hide-and-seek: Forcing a network to be meticulous for weakly-supervised object and action localization,” in ICCV , 2017
2017
Later among the works it cites.
Z. Zhong, L. Zheng, D. Cao, and S. Li, “Re-ranking person re-identification with k-reciprocal encoding,” CVPR , 2017
2017
Later among the works it cites.
Z. Zhong, L. Zheng, G. Kang, S. Li, and Y. Yang, “Random erasing data augmentation,” CoRR , 2017
2017
Later among the works it cites.
Y. Wei, J. Feng, X. Liang, M.-M. Cheng, Y. Zhao, and S. Yan, “Object region mining with adversarial erasing: A simple classification to semantic segmentation approach,” in CVPR , 2017
2017
Later among the works it cites.
X. Wang, A. Shrivastava, and A. Gupta, “A-fast-rcnn: Hard positive generation via adversary for object detection,” in CVPR , 2017
2017
Later among the works it cites.
E. Agustsson, R. Timofte, S. Escalera, X. Baro, I. Guyon, and R. Rothe, “Apparent and real age estimation in still images with deep residual regressors on appa-real database,” in FG , 2017
2017
Later among the works it cites.
A. Chaudhry, P. K. Dokania, and P. H. S. Torr, “Discovering class-specific pixels for weakly-supervised semantic segmentation,” BMVC , 2017
2017
Later among the works it cites.
X. Zhang, Y. Wei, J. Feng, Y. Yang, and T. Huang, “Adversarial complementary learning for weakly supervised object localization,” in CVPR , 2018
2018
Closest in time.
X. Zhang, Y. Wei, G. Kang, Y. Yang, and T. Huang, “Self-produced guidance for weakly-supervised object localization,” in ECCV , 2018
2018
Closest in time.
Z. Zhong, L. Zheng, Z. Zheng, S. Li, and Y. Yang, “Camera style adaptation for person re-identification,” in CVPR , 2018
2018
Closest in time.