| Faster R-CNN: Towards real-time object detection with region proposal networks S Ren, K He, R Girshick, J Sun Advances in neural information processing systems, 91-99, 2015 | 28531 | 2015 |
| Rich feature hierarchies for accurate object detection and semantic segmentation R Girshick, J Donahue, T Darrell, J Malik Proceedings of the IEEE conference on computer vision and pattern …, 2014 | 18922 | 2014 |
| Caffe: Convolutional architecture for fast feature embedding Y Jia, E Shelhamer, J Donahue, S Karayev, J Long, R Girshick, ... Proceedings of the 22nd ACM international conference on Multimedia, 675-678, 2014 | 15264 | 2014 |
| You only look once: Unified, real-time object detection J Redmon, S Divvala, R Girshick, A Farhadi Proceedings of the IEEE conference on computer vision and pattern …, 2016 | 15227 | 2016 |
| Microsoft coco: Common objects in context TY Lin, M Maire, S Belongie, J Hays, P Perona, D Ramanan, P Dollár, ... European conference on computer vision, 740-755, 2014 | 15187 | 2014 |
| Fast R-CNN R Girshick Proceedings of the IEEE International Conference on Computer Vision, 1440-1448, 2015 | 14278 | 2015 |
| Mask R-CNN K He, G Gkioxari, P Dollár, R Girshick arXiv preprint arXiv:1703.06870, 2017 | 11144 | 2017 |
| Object detection with discriminatively trained part-based models PF Felzenszwalb, RB Girshick, D McAllester, D Ramanan Pattern Analysis and Machine Intelligence, IEEE Transactions on 32 (9), 1627 …, 2010 | 10614 | 2010 |
| Focal loss for dense object detection TY Lin, P Goyal, R Girshick, K He, P Dollár Proceedings of the IEEE international conference on computer vision, 2980-2988, 2017 | 6862 | 2017 |
| Feature pyramid networks for object detection TY Lin, P Dollár, R Girshick, K He, B Hariharan, S Belongie Proceedings of the IEEE conference on computer vision and pattern …, 2017 | 6803 | 2017 |
| Aggregated residual transformations for deep neural networks S Xie, R Girshick, P Dollár, Z Tu, K He Proceedings of the IEEE conference on computer vision and pattern …, 2017 | 4028 | 2017 |
| Non-local neural networks X Wang, R Girshick, A Gupta, K He Proceedings of the IEEE conference on computer vision and pattern …, 2018 | 2668 | 2018 |
| Accurate, large minibatch sgd: Training imagenet in 1 hour P Goyal, P Dollár, R Girshick, P Noordhuis, L Wesolowski, A Kyrola, ... arXiv preprint arXiv:1706.02677, 2017 | 1606 | 2017 |
| Hypercolumns for object segmentation and fine-grained localization B Hariharan, P Arbeláez, R Girshick, J Malik Proceedings of the IEEE conference on computer vision and pattern …, 2015 | 1447 | 2015 |
| Training region-based object detectors with online hard example mining A Shrivastava, A Gupta, R Girshick Proceedings of the IEEE conference on computer vision and pattern …, 2016 | 1363 | 2016 |
| Learning rich features from RGB-D images for object detection and segmentation S Gupta, R Girshick, P Arbeláez, J Malik Computer Vision–ECCV 2014, 345-360, 2014 | 1353 | 2014 |
| Unsupervised deep embedding for clustering analysis J Xie, R Girshick, A Farhadi International conference on machine learning, 478-487, 2016 | 1126 | 2016 |
| Simultaneous detection and segmentation B Hariharan, P Arbeláez, R Girshick, J Malik European Conference on Computer Vision, 297-312, 2014 | 1093 | 2014 |
| Cascade object detection with deformable part models PF Felzenszwalb, RB Girshick, D McAllester Computer vision and pattern recognition (CVPR), 2010 IEEE conference on …, 2010 | 1022 | 2010 |
| Inside-outside net: Detecting objects in context with skip pooling and recurrent neural networks S Bell, CL Zitnick, K Bala, R Girshick Proceedings of the IEEE conference on computer vision and pattern …, 2016 | 958 | 2016 |
Kaiming HeResearch Scientist, Facebook AI Research (FAIR)在 fb.com 的电子邮件经过验证
