Fetching the paper…
Reading the bibliography…
Given the wide diffusion of deep neural network architectures for computer vision tasks, several new applications are nowadays more and more feasible.
R. Girshick, J. Donahue, T. Darrell, and J. Malik, “Rich feature hierarchies for accurate object detection and semantic segmentation,” in Proceedings of the IEEE conference on computer vision and pattern recognition , 2014, pp. 580–587
2014
Earlier work this paper cites.
T.-Y. Lin, M. Maire, S. Belongie, J. Hays, P. Perona, D. Ramanan, P. Dollár, and C. L. Zitnick, “Microsoft coco: Common objects in context,” in European conference on computer vision . Springer, 2014, pp. 740–755
2014
Earlier work this paper cites.
R. Girshick, “Fast r-cnn,” in Proceedings of the IEEE international conference on computer vision , 2015, pp. 1440–1448
2015
Earlier work this paper cites.
S. Ren, K. He, R. Girshick, and J. Sun, “Faster r-cnn: Towards real-time object detection with region proposal networks,” in Advances in neural information processing systems , 2015, pp. 91–99
2015
Earlier work this paper cites.
B. Hariharan, P. Arbeláez, R. Girshick, and J. Malik, “Hypercolumns for object segmentation and fine-grained localization,” in Proceedings of the IEEE conference on computer vision and pattern recognition , 2015, pp. 447–456
2015
Earlier work this paper cites.
J. Dai, K. He, and J. Sun, “Instance-aware semantic segmentation via multi-task network cascades,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 2016, pp. 3150–3158
2016
Earlier work this paper cites.
J. Pont-Tuset, P. Arbelaez, J. T. Barron, F. Marques, and J. Malik, “Multiscale combinatorial grouping for image segmentation and object proposal generation,” IEEE transactions on pattern analysis and machine intelligence , vol. 39, no. 1, pp. 128–140, 2016
2016
Earlier work this paper cites.
S. Ren, K. He, R. Girshick, X. Zhang, and J. Sun, “Object detection networks on convolutional feature maps,” IEEE transactions on pattern analysis and machine intelligence , vol. 39, no. 7, pp. 1476–1481, 2016
2016
Earlier work this paper cites.
P. O. Pinheiro, T.-Y. Lin, R. Collobert, and P. Dollár, “Learning to refine object segments,” in European Conference on Computer Vision . Springer, 2016, pp. 75–91
2016
Earlier work this paper cites.
S. Bell, C. Lawrence Zitnick, K. Bala, and R. Girshick, “Inside-outside net: Detecting objects in context with skip pooling and recurrent neural networks,” in Proceedings of the IEEE conference on computer vision and pattern recognition , 2016, pp. 2874–2883
2016
Cited alongside, same era.
K. He, X. Zhang, S. Ren, and J. Sun, “Deep residual learning for image recognition,” in Proceedings of the IEEE conference on computer vision and pattern recognition , 2016, pp. 770–778
2016
Cited alongside, same era.
K. He, G. Gkioxari, P. Dollár, and R. Girshick, “Mask r-cnn,” in Proceedings of the IEEE international conference on computer vision , 2017, pp. 2961–2969
2017
Cited alongside, same era.
T.-Y. Lin, P. Dollár, R. Girshick, K. He, B. Hariharan, and S. Belongie, “Feature pyramid networks for object detection,” in Proceedings of the IEEE conference on computer vision and pattern recognition , 2017, pp. 2117–2125
2017
Cited alongside, same era.
X. Lu, B. Li, Y. Yue, Q. Li, and J. Yan, “Grid r-cnn,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 2019, pp. 7363–7372
2019
Later among the works it cites.
Z. Cai and N. Vasconcelos, “Cascade r-cnn: High quality object detection and instance segmentation,” IEEE Transactions on Pattern Analysis and Machine Intelligence , 2019
2019
Later among the works it cites.
K. Chen, J. Pang, J. Wang, Y. Xiong, X. Li, S. Sun, W. Feng, Z. Liu, J. Shi, W. Ouyang et al. , “Hybrid task cascade for instance segmentation,” in Proceedings of the IEEE conference on computer vision and pattern recognition , 2019, pp. 4974–4983
2019
Later among the works it cites.
Y. Cao, J. Xu, S. Lin, F. Wei, and H. Hu, “Gcnet: Non-local networks meet squeeze-excitation networks and beyond,” in Proceedings of the IEEE International Conference on Computer Vision Workshops , 2019, pp. 0–0
2019
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
2017
Cited alongside, same era.
B. Jiang, R. Luo, J. Mao, T. Xiao, and Y. Jiang, “Acquisition of localization confidence for accurate object detection,” in Proceedings of the European Conference on Computer Vision (ECCV) , 2018, pp. 784–799
2018
Cited alongside, same era.
S. Liu, L. Qi, H. Qin, J. Shi, and J. Jia, “Path aggregation network for instance segmentation,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 2018, pp. 8759–8768
2018
Cited alongside, same era.
T. D. Linh and M. Arai, “Multi-scale subnetwork for roi pooling for instance segmentation,” International Journal of Computer Theory and Engineering , vol. 10, no. 6, 2018
2018
Cited alongside, same era.
X. Wang, R. Girshick, A. Gupta, and K. He, “Non-local neural networks,” in Proceedings of the IEEE conference on computer vision and pattern recognition , 2018, pp. 7794–7803
2018
Cited alongside, same era.
H. Xu, L. Yao, W. Zhang, X. Liang, and Z. Li, “Auto-fpn: Automatic network architecture adaptation for object detection beyond classification,” in Proceedings of the IEEE International Conference on Computer Vision , 2019, pp. 6649–6658
2019
Later among the works it cites.
2019
Later among the works it cites.
X. Zhu, D. Cheng, Z. Zhang, S. Lin, and J. Dai, “An empirical study of spatial attention mechanisms in deep networks,” in Proceedings of the IEEE International Conference on Computer Vision , 2019, pp. 6688–6697
2019
Later among the works it cites.
2019
Later among the works it cites.