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Weakly supervised object localization (WSOL) is a challenging problem which aims to localize objects with only image-level labels.
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C. L. Zitnick, P. Dollár, Edge boxes: Locating object proposals from edges, in: D. Fleet, T. Pajdla, B. Schiele, T. Tuytelaars (Eds.), Computer Vision – ECCV 2014, 2014, pp. 391–405
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C. Szegedy, W. Liu, Y. Jia, P. Sermanet, S. Reed, D. Anguelov, D. Erhan, V. Vanhoucke, A. Rabinovich, Going deeper with convolutions, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015
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B. Zhou, A. Khosla, A. Lapedriza, A. Oliva, A. Torralba, Learning deep features for discriminative localization, in: The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016
2016
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H. Bilen, A. Vedaldi, Weakly supervised deep detection networks, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016
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C. Feichtenhofer, A. Pinz, A. Zisserman, Convolutional two-stream network fusion for video action recognition, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016
2016
Cited alongside, same era.
K. Kumar Singh, Y. Jae Lee, Hide-and-seek: Forcing a network to be meticulous for weakly-supervised object and action localization, in: The IEEE International Conference on Computer Vision (ICCV), 2017
2017
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P. Tang, X. Wang, X. Bai, W. Liu, Multiple instance detection network with online instance classifier refinement, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017
2017
Cited alongside, same era.
A. Diba, V. Sharma, A. Pazandeh, H. Pirsiavash, L. Van Gool, Weakly supervised cascaded convolutional networks, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017
2017
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F. Wan, P. Wei, J. Jiao, Z. Han, Q. Ye, Min-entropy latent model for weakly supervised object detection, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018
2018
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Y. Zhang, Y. Bai, M. Ding, Y. Li, B. Ghanem, W2f: A weakly-supervised to fully-supervised framework for object detection, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018
2018
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J. Choe, H. Shim, Attention-based dropout layer for weakly supervised object localization, in: The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019
2019
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C. Feichtenhofer, A. Pinz, A. Zisserman, Densefuse: A fusion approach to infrared and visible images, in: IEEE Transactions on Image Processing, vol. 28, no. 5, pp. 2614-2623,, 2019
2019
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X. Zhang, Y. Wei, J. Feng, Y. Yang, T. Huang, Adversarial complementary learning for weakly supervised object localization, in: IEEE CVPR, 2018
2018
Cited alongside, same era.
X. Zhang, Y. Wei, G. Kang, Y. Yang, T. Huang, Self-produced guidance for weakly-supervised object localization, in: The European Conference on Computer Vision (ECCV), 2018
2018
Cited alongside, same era.
Y. Wei, Z. Shen, B. Cheng, H. Shi, J. Xiong, J. Feng, T. S. Huang, Ts2c: Tight box mining with surrounding segmentation context for weakly supervised object detection , in: ECCV (11), 2018, pp. 454–470. URL https://doi.org/10.1007/978-3-030-01252-6_27
2018
Cited alongside, same era.
Cited in the paper.
Z. Li, F. Zhou, Fssd: Feature fusion single shot multibox detector, ArXiv abs/1712.00960
Cited in the paper.
doi:10.1007/s11263-012-0538-3
T. Deselaers, B. Alexe, V. Ferrari, Weakly supervised localization and learning with generic knowledge, International Journal of Computer Vision 100
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K. Simonyan, A. Zisserman, Very deep convolutional networks for large-scale image recognition, arXiv 1409.1556
Cited in the paper.
F. Wan, C. Liu, W. Ke, X. Ji, J. Jiao, Q. Ye, C-mil: Continuation multiple instance learning for weakly supervised object detection, in: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019
2019
Later among the works it cites.
J. Whitehill, T. fan Wu, J. Bergsma, J. R. Movellan, P. L. Ruvolo, Whose vote should count more: Optimal integration of labels from labelers of unknown expertise, in: Y. Bengio, D. Schuurmans, J. D. Lafferty, C. K. I. Williams, A. Culotta (Eds.), Advances in Neural Information Processing Systems 22, Curran Associates, Inc., 2009, pp. 2035–2043
2043
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