Fetching the paper…
Reading the bibliography…
In a weakly-supervised scenario object detectors need to be trained using image-level annotation alone.
The Pascal Visual Object Classes Challenge 2007 (VOC 2007) Results
M. Everingham, L. Van Gool, C. K. Williams, J. Winn, and A. Zisserman · 2007
Earlier work this paper cites.
Curriculum learning
Y. Bengio, J. Louradour, R. Collobert, and J. Weston · 2009
Earlier work this paper cites.
The Pascal Visual Object Classes (VOC) challenge
M. Everingham, L. Van Gool, C. K. Williams, J. Winn, and A. Zisserman · 2010
Earlier work this paper cites.
Self-paced learning for latent variable models
M. P. Kumar, B. Packer, and D. Koller · 2010
Earlier work this paper cites.
Learning the easy things first: Self-paced visual category discovery
Y. J. Lee and K. Grauman · 2011
Earlier work this paper cites.
Ensemble of Exemplar-SVMs for object detection and beyond
T. Malisiewicz, A. Gupta, and A. A. Efros · 2011
Earlier work this paper cites.
Undoing the damage of dataset bias
A. Khosla, T. Zhou, T. Malisiewicz, A. Efros, and A. Torralba · 2012
Earlier work this paper cites.
ImageNet classification with deep convolutional neural networks
A. Krizhevsky, I. Sutskever, and G. E. Hinton · 2012
Earlier work this paper cites.
Are all training examples equally valuable?
À. Lapedriza, H. Pirsiavash, Z. Bylinskii, and A. Torralba · 2013
Earlier work this paper cites.
Self-paced learning for long-term tracking
J. S. Supancic III and D. Ramanan · 2013
Earlier work this paper cites.
Selective search for object recognition
J. R. R. Uijlings, K. E. A. van de Sande, T. Gevers, and A. W. M. Smeulders · 2013
Earlier work this paper cites.
Weakly supervised object detection with posterior regularization
H. Bilen, M. Pedersoli, and T. Tuytelaars · 2014
Earlier work this paper cites.
Return of the devil in the details: Delving deep into convolutional nets
K. Chatfield, K. Simonyan, A. Vedaldi, and A. Zisserman · 2014
Earlier work this paper cites.
Multi-fold MIL training for weakly supervised object localization
R. G. Cinbis, J. J. Verbeek, and C. Schmid · 2014
Earlier work this paper cites.
Rich feature hierarchies for accurate object detection and semantic segmentation
R. B. Girshick, J. Donahue, T. Darrell, and J. Malik · 2014
Earlier work this paper cites.
LSDA: large scale detection through adaptation
J. Hoffman, S. Guadarrama, E. Tzeng, R. Hu, J. Donahue, R. B. Girshick, T. Darrell, and K. Saenko · 2014
Cited alongside, same era.
Self-paced learning with diversity
L. Jiang, D. Meng, S. Yu, Z. Lan, S. Shan, and A. G. Hauptmann · 2014
Cited alongside, same era.
Learning discriminative localization from weakly labeled data
M. H. Nguyen, L. Torresani, F. D. la Torre, and C. Rother · 2014
Cited alongside, same era.
Imagenet large scale visual recognition challenge
O. Russakovsky, J. Deng, H. Su, J. Krause, S. Satheesh, S. Ma, Z. Huang, A. Karpathy, A. Khosla, M. S. Bernstein, A. C. Berg, and F. Li · 2014
Cited alongside, same era.
Statistical and spatial consensus collection for detector adaptation
E. Sangineto · 2014
Cited alongside, same era.
Very deep convolutional networks for large-scale image recognition
Is object localization for free? - Weakly-supervised learning with convolutional neural networks
M. Oquab, L. Bottou, I. Laptev, and J. Sivic · 2015
Later among the works it cites.
Curriculum learning of multiple tasks
A. Pentina, V. Sharmanska, and C. H. Lampert · 2015
Later among the works it cites.
FaceNet: A unified embedding for face recognition and clustering
F. Schroff, D. Kalenichenko, and J. Philbin · 2015
Later among the works it cites.
Large-scale weakly supervised object localization via latent category learning
C. Wang, K. Huang, W. Ren, J. Zhang, and S. J. Maybank · 2015
Later among the works it cites.
Self-taught object localization with deep networks
L. Bazzani, A. Bergamo, D. Anguelov, and L. Torresani · 2016
Closest in time.
Weakly supervised deep detection networks
H. Bilen and A. Vedaldi · 2016
Closest in time.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
K. Simonyan and A. Zisserman · 2014
Cited alongside, same era.
On learning to localize objects with minimal supervision
H. O. Song, R. Girshick, S. Jegelka, J. Mairal, Z. Harchaoui, and T. Darrell · 2014
Cited alongside, same era.
Weakly-supervised discovery of visual pattern configurations
H. O. Song, Y. J. Lee, S. Jegelka, and T. Darrell · 2014
Cited alongside, same era.
W. Zaremba and I. Sutskever · 2014
Cited alongside, same era.
Weakly supervised object detection with convex clustering
H. Bilen, M. Pedersoli, and T. Tuytelaars · 2015
Cited alongside, same era.
Webly supervised learning of convolutional networks
X. Chen and A. Gupta · 2015
Cited alongside, same era.
Fast R-CNN
R. B. Girshick · 2015
Cited alongside, same era.
ContextLocNet: context-aware deep network models for weakly supervised localization
V. Kantorov, M. Oquab, M. Cho, and I. Laptev · 2016
Closest in time.
Weakly supervised object localization with progressive domain adaptation
D. Li, J.-B. Huang, Y. Li, S. Wang, and M.-H. Yang · 2016
Closest in time.
Weakly supervised object localization using size estimates
M. Shi and V. Ferrari · 2016
Closest in time.
Training region-based object detectors with online hard example mining
A. Shrivastava, A. Gupta, and R. Girshick · 2016
Closest in time.
Attention networks for weakly supervised object localization
E. W. Teh, M. Rochan, and Y. Wang · 2016
Closest in time.
D. Zhang, D. Meng, L. Zhao, and J. Han · 2016
Closest in time.
Weakly supervised object localization with multi-fold multiple instance learning
R. G. Cinbis, J. J. Verbeek, and C. Schmid · 2017
Closest in time.
Mask R-CNN
K. He, G. Gkioxari, P. Dollár, and R. B. Girshick · 2017
Closest in time.
STC: A simple to complex framework for weakly-supervised semantic segmentation
Y. Wei, X. Liang, Y. Chen, X. Shen, M. Cheng, J. Feng, Y. Zhao, and S. Yan · 2017
Closest in time.