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Object detection has achieved promising success, but requires large-scale fully-annotated data, which is time-consuming and labor-extensive.
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.
Weakly supervised localization and learning with generic knowledge
Thomas Deselaers, Bogdan Alexe, and Vittorio Ferrari · 2012
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Large-scale knowledge transfer for object localization in imagenet
M. Guillaumin and V. Ferrari · 2012
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Transfer learning by ranking for weakly supervised object annotation
Z. Shi, P. Siva, and T. Xiang · 2012
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Selective search for object recognition
Jasper RR Uijlings, Koen EA Van De Sande, Theo Gevers, and Arnold WM Smeulders · 2013
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Rich feature hierarchies for accurate object detection and semantic segmentation
Ross Girshick, Jeff Donahue, Trevor Darrell, and Jitendra Malik · 2014
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Lsda: Large scale detection through adaptation
Judy Hoffman, Sergio Guadarrama, Eric Tzeng, Ronghang Hu, Jeff Donahue, Ross Girshick, Trevor Darrell, and Kate Saenko · 2014
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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.
Edge boxes: Locating object proposals from edges
C Lawrence Zitnick and Piotr Dollár · 2014
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Fast r-cnn
Ross Girshick · 2015
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Faster R-CNN: Towards real-time object detection with region proposal networks
Shaoqing Ren, Kaiming He, Ross Girshick, and Jian Sun · 2015
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Weakly supervised localization of novel objects using appearance transfer
M. Rochan and W. Yang · 2015
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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, Alexander C. Berg, and Li Fei-Fei · 2015
Earlier work this paper cites.
Weakly supervised deep detection networks
Hakan Bilen and Andrea Vedaldi · 2016
Earlier work this paper cites.
Weakly supervised object localization with progressive domain adaptation
L. Dong, J. B. Huang, Y. Li, S. Wang, and M. H. Yang · 2016
Earlier work this paper cites.
Deep residual learning for image recognition
K. He, X. Zhang, S. Ren, and J. Sun · 2016
Earlier work this paper cites.
Large scale semi-supervised object detection using visual and semantic knowledge transfer
Y. Tang, J. Wang, B. Gao, E Dellandréa, R. Gaizauskas, and L. Chen · 2016
Earlier work this paper cites.
Learning deep features for discriminative localization
Bolei Zhou, Aditya Khosla, Agata Lapedriza, Aude Oliva, and Antonio Torralba · 2016
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Weakly supervised cascaded convolutional networks
Ali Diba, Vivek Sharma, Ali Pazandeh, Hamed Pirsiavash, and Luc Van Gool · 2017
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Weakly supervised object localization using things and stuff transfer
M. Shi, H. Caesar, and V. Ferrari · 2017
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Hide-and-seek: Forcing a network to be meticulous for weakly-supervised object and action localization
K. K. Singh and J. L. Yong · 2017
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Multiple instance detection network with online instance classifier refinement
Peng Tang, Xinggang Wang, Xiang Bai, and Wenyu Liu · 2017
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Multi-evidence filtering and fusion for multi-label classification, object detection and semantic segmentation based on weakly supervised learning
Cyclic guidance for weakly supervised joint detection and segmentation
Yunhang Shen, Rongrong Ji, Yan Wang, Yongjian Wu, and Liujuan Cao · 2019
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Fcos: Fully convolutional one-stage object detection
Zhi Tian, Chunhua Shen, Hao Chen, and Tong He · 2019
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Large-scale knowledge transfer for object localization in imagenet
N. Araslanov and S. Roth · 2020
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Cross-supervised object detection
Zitian Chen, Zhiqiang Shen, Jiahui Yu, and Erik Learned-Miller · 2020
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Attention-based dropout layer for weakly supervised single object localization and semantic segmentation
J. Choe, S. Lee, and H. Shim · 2020
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Weifeng Ge, Sibei Yang, and Yizhou Yu · 2018
Cited alongside, same era.
Learning to segment every thing
Ronghang Hu, Piotr Dollár, Kaiming He, Trevor Darrell, and Ross Girshick · 2018
Cited alongside, same era.
Weakly-supervised semantic segmentation network with deep seeded region growing
Z. Huang, X. Wang, J. Wang, W. Liu, and J. Wang · 2018
Cited alongside, same era.
Cross-domain weakly-supervised object detection through progressive domain adaptation
Naoto Inoue, Ryosuke Furuta, Toshihiko Yamasaki, and Kiyoharu Aizawa · 2018
Cited alongside, same era.
Mixed supervised object detection with robust objectness transfer
Yan Li, Junge Zhang, Kaiqi Huang, and Jianguo Zhang · 2018
Cited alongside, same era.
Pcl: Proposal cluster learning for weakly supervised object detection
Peng Tang, Xinggang Wang, Song Bai, Wei Shen, Xiang Bai, Wenyu Liu, and Alan Yuille · 2018
Cited alongside, same era.
Revisiting knowledge transfer for training object class detectors
J. Uijlings, S. Popov, and V. Ferrari · 2018
Cited alongside, same era.
Nicolas Gonthier, Saïd Ladjal, and Yann Gousseau · 2020
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Comprehensive attention self-distillation for weakly-supervised object detection
Zeyi Huang, Yang Zou, BVK Kumar, and Dong Huang · 2020
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Scaling object detection by transferring classification weights
J. Kuen, F. Perazzi, Z. Lin, J. Zhang, and Y. P. Tan · 2020
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Instance-aware, context-focused, and memory-efficient weakly supervised object detection
Zhongzheng Ren, Zhiding Yu, Xiaodong Yang, Ming-Yu Liu, Yong Jae Lee, Alexander G Schwing, and Jan Kautz · 2020
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Enabling deep residual networks for weakly supervised object detection
Y. Shen, R. Ji, Y. Wang, Z. Chen, and Y. Wu · 2020
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Boosting weakly supervised object detection with progressive knowledge transfer
Yuanyi Zhong, Jianfeng Wang, Jian Peng, and Lei Zhang · 2020
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Comprehensive attention self-distillation for weakly-supervised object detection
Zeyi Huang, Yang Zou, BVK Kumar, and Dong Huang · 2020
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Boosting weakly supervised object detection with progressive knowledge transfer
Yuanyi Zhong, Jianfeng Wang, Jian Peng, and Lei Zhang · 2020
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Weak-shot fine-grained classification via similarity transfer
Junjie Chen, Li Niu, Liu Liu, and Liqing Zhang · 2021
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Puzzle-cam: Improved localization via matching partial and full features
Sanghyun Jo and In-Jae Yu · 2021
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Weak-shot semantic segmentation by transferring semantic affinity and boundary
Siyuan Zhou, Li Niu, Jianlou Si, Chen Qian, and Liqing Zhang · 2021
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