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Efficient and reliable methods for training of object detectors are in higher demand than ever, and more and more data relevant to the field is becoming available.
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.
Weakly supervised object detector learning with model drift detection
P. Siva and T. Xiang · 2011
Earlier work this paper cites.
Transfer learning by ranking for weakly supervised object annotation
Z. Shi, P. Siva, and T. Xiang · 2012
Earlier work this paper cites.
Microsoft coco: Common objects in context
T.-Y. Lin, M. Maire, S. Belongie, L. Bourdev, R. Girshick, J. Hays, P. Perona, D. Ramanan, C. L. Zitnick, and P. Dollár · 2014
Earlier work this paper cites.
Overfeat: Integrated recognition, localization and detection using convolutional networks
P. Sermanet, D. Eigen, X. Zhang, M. Mathieu, R. Fergus, and Y. LeCun · 2014
Earlier work this paper cites.
Co-localization in real-world images
K. Tang, A. Joulin, L.-J. Li, and L. Fei-Fei · 2014
Earlier work this paper cites.
Fast r-cnn
R. Girshick · 2015
Earlier work this paper cites.
Faster r-cnn: Towards real-time object detection with region proposal networks
S. Ren, K. He, R. Girshick, and J. Sun · 2015
Earlier work this paper cites.
Chainer: a next-generation open source framework for deep learning
S. Tokui, K. Oono, S. Hido, and J. Clayton · 2015
Earlier work this paper cites.
Weakly supervised deep detection networks
H. Bilen and A. Vedaldi · 2016
Earlier work this paper cites.
Weakly supervised object localization with multi-fold multiple instance learning
R. G. Cinbis, J. Verbeek, and C. Schmid · 2016
Cited alongside, same era.
Deep residual learning for image recognition
K. He, X. Zhang, S. Ren, and J. Sun · 2016
Cited alongside, same era.
Ssd: Single shot multibox detector
W. Liu, D. Anguelov, D. Erhan, C. Szegedy, S. Reed, C.-Y. Fu, and A. C. Berg · 2016
Cited alongside, same era.
You only look once: Unified, real-time object detection
J. Redmon, S. Divvala, R. Girshick, and A. Farhadi · 2016
Cited alongside, same era.
Training region-based object detectors with online hard example mining
A. Shrivastava, A. Gupta, and R. Girshick · 2016
Cited alongside, same era.
ChainerMN: Scalable Distributed Deep Learning Framework
T. Akiba, K. Fukuda, and S. Suzuki · 2017
Cited alongside, same era.
Weakly- and semi-supervised object detection with expectation-maximization algorithm
Z. Yan, J. Liang, W. Pan, J. Li, and C. Zhang · 2017
Later among the works it cites.
Couplenet: Coupling global structure with local parts for object detection
Y. Zhu, C. Zhao, J. Wang, X. Zhao, Y. Wu, H. Lu, et al · 2017
Later among the works it cites.
Y. Gao, X. Bu, Y. Hu, H. Shen, T. Bai, X. Li, and S. Wen · 2018
Closest in time.
Squeeze-and-excitation networks
J. Hu, L. Shen, and G. Sun · 2018
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Cross-domain weakly-supervised object detection through progressive domain adaptation
N. Inoue, R. Furuta, T. Yamasaki, and K. Aizawa · 2018
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Object detection meets knowledge graphs
Y. Fang, K. Kuan, J. Lin, C. Tan, and V. Chandrasekhar · 2017
Cited alongside, same era.
Feature pyramid networks for object detection
T.-Y. Lin, P. Dollár, R. B. Girshick, K. He, B. Hariharan, and S. J. Belongie · 2017
Cited alongside, same era.
Chainercv: a library for deep learning in computer vision
Y. Niitani, T. Ogawa, S. Saito, and M. Saito · 2017
Cited alongside, same era.
A. Kuznetsova, H. Rom, N. Alldrin, J. Uijlings, I. Krasin, J. Pont-Tuset, S. Kamali, S. Popov, M. Malloci, T. Duerig, and V. Ferrari · 2018
Closest in time.
Focal loss for dense object detection
T.-Y. Lin, P. Goyal, R. Girshick, K. He, and P. Dollár · 2018
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Soft sampling for robust object detection
Z. Wu, N. Bodla, B. Singh, M. Najibi, R. Chellappa, and L. S. Davis · 2018
Closest in time.
Part-aware fine-grained object categorization using weakly supervised part detection network
Y. Zhang, K. Jia, and Z. Wang · 2018
Closest in time.