| 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 | 100140 | 2015 |
| 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 | 71288 | 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 | 67337 | 2014 |
| 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 | 49394 | 2014 |
| Mask R-CNN K He, G Gkioxari, P Dollár, R Girshick arXiv preprint arXiv:1703.06870, 2017 | 48592 | 2017 |
| 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 | 44943 | 2017 |
| Fast R-CNN R Girshick Proceedings of the IEEE International Conference on Computer Vision, 1440-1448, 2015 | 44308 | 2015 |
| 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 | 37313 | 2017 |
| 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 | 18926 | 2014 |
| Momentum contrast for unsupervised visual representation learning K He, H Fan, Y Wu, S Xie, R Girshick Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 18372 | 2020 |
| Segment anything A Kirillov, E Mintun, N Ravi, H Mao, C Rolland, L Gustafson, T Xiao, ... Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 17179 | 2023 |
| 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 | 16102 | 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 | 14006 | 2010 |
| Non-local neural networks X Wang, R Girshick, A Gupta, K He Proceedings of the IEEE conference on computer vision and pattern …, 2018 | 13570 | 2018 |
| Masked autoencoders are scalable vision learners K He, X Chen, S Xie, Y Li, P Dollár, R Girshick Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 13167 | 2022 |
| 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 | 4880 | 2017 |
| Improved baselines with momentum contrastive learning X Chen, H Fan, R Girshick, K He arXiv preprint arXiv:2003.04297, 2020 | 4589 | 2020 |
| Unsupervised deep embedding for clustering analysis J Xie, R Girshick, A Farhadi International conference on machine learning, 478-487, 2016 | 4496 | 2016 |
| Detectron2 Y Wu, A Kirillov, F Massa, WY Lo, R Girshick | 3883 | 2019 |
| 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 | 3356 | 2016 |
Kaiming HeAssociate Professor, EECS, MITVerified email at mit.edu
