Fetching the paper…
Reading the bibliography…
As the post-processing step for object detection, non-maximum suppression (GreedyNMS) is widely used in most of the detectors for many years.
1901
Earlier work this paper cites.
Y. LeCun, L. Bottou, Y. Bengio, and P. Haffner, “Gradient-based learning applied to document recognition,” IJCV , vol. 86, no. 11, pp. 2278–2324, 1998
1998
Earlier work this paper cites.
B. Leibe, K. Schindler, and L. V. Gool, “Coupled detection and trajectory estimation for multi-object tracking,” in ICCV , 2007
2007
Earlier work this paper cites.
A. B. Chan, Z.-S. J. Liang, and N. Vasconcelos, “Privacy preserv- ing crowd monitoring: Counting people without people mod- els or tracking,” in CVPR , 2008
2008
Earlier work this paper cites.
M. Andriluka, S. Roth, and B. Schiele, “People-tracking-by-detection and people-detection-by-tracking,” in CVPR , 2008
2008
Earlier work this paper cites.
P. Felzenszwal, R. Girshick, and D. McAllester, “Object detection with discriminatively trained part-based models,” TPAMI , vol. 32, no. 9, pp. 1627–1645, 2010
2010
Earlier work this paper cites.
M. A. Sadeghi and A. Farhadi, “Recognition using visual phrases,” in CVPR , 2011
2011
Earlier work this paper cites.
M. Rodriguez, I. Laptev, and J. Sivic, “Density-aware person detection and tracking in crowds,” in ICCV , 2011
2011
Earlier work this paper cites.
H. Pirsiavash, D. Ramanan, and C. C. Fowlkes, “Globally optimal greedy algorithms for tracking a variable number of objects,” in CVPR , 2011
2011
Earlier work this paper cites.
A. R. Zamir, A. Dehghan, and M. Shah, “GMCP-Tracker: global multi-object tracking using generalized minimum clique graphs,” ECCV , 2012
2012
Earlier work this paper cites.
A. Krizhevsky, I. Sutskever, and G. E. Hinton, “Imagenet classification with deep convolutional neural networks,” in NIPS , 2012
2012
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 , 2012
2012
Earlier work this paper cites.
O. Barinova, V. Lempitsky, and P. Kholi, “On detection of multiple object instances using hough transforms,” TPAMI , vol. 34, no. 9, pp. 1773–1784, 2012
2012
Earlier work this paper cites.
S. Tang, M. Andriluka, A. Milan, K. Schindler, S. Roth, and B. Schiele, “Learning people detectors for tracking in crowded scenes,” in ICCV , 2013
2013
Cited alongside, same era.
W. Ouyang and X. Wang, “Single-pedestrian detection aided by multi-pedestrian detection,” in CVPR , 2013
2013
Cited alongside, same era.
M. Lin, Q. Chen, and S. Yan, “Network in network,” in arXiv preprint arXiv:1312.4400 , 2013
2013
Cited alongside, same era.
K. He, X. Zhang, S. Ren, and J. Sun, “Spatial pyramid pooling in deep convolutional networks for visual recognition,” in ECCV , 2014
2014
Cited alongside, same era.
T.-Y. Lin, M. Maire, S. Belongie, L. Bourdev, R. Girshick, J. Hays, P. Perona, D. Ramanan, C. L. Zitnick, and P. Dollar, “Microsoft COCO: common objects in context,” in ECCV , 2014
2014
2015
Later among the works it cites.
K. He, X. Zhang, S. Ren, and J. Sun, “Deep residual learning for image recognition,” in CVPR , 2016
2016
Later among the works it cites.
T. T. Pham, S. H. Rezatofighi, I. Reid, and T.-J. Chin, “Efficient point process inference for large-scale object detection,” in CVPR , 2016
2016
Later among the works it cites.
J. Hosang, R. Benenson, and B. Schiele, “A convnet for non-maximum suppression,” in GCPR , 2016
2016
Later among the works it cites.
C. Szegedy, V. Vanhoucke, S. Ioffe, J. Shlens, and Z. Wojna, “Rethinking the inception architecture for computer vision,” in Proceedings of the IEEE conference on computer vision and pattern recognition , 2016, pp. 2818–2826
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
R. Rothe, M. Guillaumin, and L. V. Gool, “Non-maximum suppression for object detection by passing messages between windows,” in ACCV , 2014
2014
Cited alongside, same era.
2014
Cited alongside, same era.
O. Russakovsky, J. Deng, H. Su, J. Krause, S. Satheesh, S. Ma, Z. Huang, A. Karpathy, A. Khosla, M. Bernstein, A. C. Berg, and L. Fei-Fei, “Imagenet large scale visual recognition challenge,” IJCV , vol. 115, no. 3, pp. 211–252, 2015
2015
Cited alongside, same era.
R. Girshick, “Fast R-CNN,” in ICCV , 2015
2015
Cited alongside, same era.
S. Ren, K. He, R. Girshick, and J. Sun, “Faster R-CNN: Towards real-time object detection with region proposal networks,” in NIPS , 2015
2015
Cited alongside, same era.
M. Everingham, S. M. A. Eslami, L. V. Gool, C. K. I. Williams, J. Winn, and A. Zisserman, “The pascal visual object classes challenge: A retrospective,” IJCV , vol. 111, no. 1, pp. 98–136, 2015
2015
Cited alongside, same era.
2015
Cited alongside, same era.
2016
Later among the works it cites.
A. Arnab and P. H. Torr, “Pixelwise instance segmentation with a dynamically instantiated network,” in CVPR , 2017
2017
Later among the works it cites.
K. He, G. Gkioxari, P. Dollar, and R. Girshick, “Mask R-CNN,” in ICCV , 2017
2017
Later among the works it cites.
M. B. R. Urtasun, “Deep watershed transform for instance segmentation,” in CVPR , 2017
2017
Later among the works it cites.
T.-Y. Lin, P. Dollar, R. Girshick, K. He, B. Hariharan, and S. Belongie, “Feature pyramid networks for object detection,” in CVPR , 2017
2017
Later among the works it cites.
N. Bodla, B. Singh, R. Chellappa, and L. S. Davis, “Soft-NMS– improving object detection with one line of code,” in ICCV , 2017
2017
Later among the works it cites.
S. H. Rezatofighi, V. Kuma, A. Milan, E. Abbasnejad, A. Dick, and I. Reid, “DeepSetNet: predicting sets with deep neural networks,” in ICCV , 2017
2017
Later among the works it cites.
——, “Learning non-maximum suppression,” in CVPR , 2017
2017
Later among the works it cites.