| Focal Loss for Dense Object Detection TY Lin, P Goyal, R Girshick, K He, P Dollár arXiv preprint arXiv:1708.02002, 2017 | 21232 | 2017 |
| Accurate, Large Minibatch SGD: Training ImageNet in 1 Hour P Goyal, P Dollár, R Girshick, P Noordhuis, L Wesolowski, A Kyrola, ... https://arxiv.org/abs/1706.02677, 2017 | 3220 | 2017 |
| Unsupervised learning of visual features by contrasting cluster assignments M Caron, I Misra, J Mairal, P Goyal, P Bojanowski, A Joulin Advances in neural information processing systems 33, 9912-9924, 2020 | 2237 | 2020 |
| Tensor comprehensions: Framework-agnostic high-performance machine learning abstractions N Vasilache, O Zinenko, T Theodoridis, P Goyal, Z DeVito, WS Moses, ... arXiv preprint arXiv:1802.04730, 2018 | 393 | 2018 |
| Scaling and Benchmarking Self-Supervised Visual Representation Learning P Goyal, D Mahajan, A Gupta, I Misra https://arxiv.org/abs/1905.01235, 2019 | 371 | 2019 |
| Self-supervised pretraining of visual features in the wild P Goyal, M Caron, B Lefaudeux, M Xu, P Wang, V Pai, M Singh, ... arXiv preprint arXiv:2103.01988, 2021 | 185 | 2021 |
| Focal loss for dense object detection. arXiv 2017 TY Lin, P Goyal, R Girshick, K He, P Dollár arXiv preprint arXiv:1708.02002, 2002 | 95 | 2002 |
| Accurate, large minibatch sgd: Training imagenet in 1 hour. arXiv 2017 P Goyal, P Dollár, R Girshick, P Noordhuis, L Wesolowski, A Kyrola, ... arXiv preprint arXiv:1706.02677, 2019 | 74 | 2019 |
| Focal loss for dense object detection. 2017 TY Lin, P Goyal, R Girshick, K He, P Dollár arXiv preprint arXiv:1708.02002, 2002 | 66 | 2002 |
| Piotr Doll ar. Focal loss for dense object detection TY Lin, P Goyal, R Girshick, K He Proceedings of the IEEE International Conference on Computer Vision (ICCV …, 2017 | 62 | 2017 |
| The next 700 accelerated layers: From mathematical expressions of network computation graphs to accelerated gpu kernels, automatically N Vasilache, O Zinenko, T Theodoridis, P Goyal, Z Devito, WS Moses, ... ACM Transactions on Architecture and Code Optimization (TACO) 16 (4), 1-26, 2019 | 56 | 2019 |
| Focal loss for dense object detection. arXiv TY Lin, P Goyal, R Girshick, K He, P Dollár arXiv preprint arXiv:1708.02002, 2017 | 55 | 2017 |
| VISSL P Goyal, B Lefaudeux, M Singh, J Reizenstein, V Reis, M Xu, M Leavitt, ... | 54 | 2021 |
| Vision models are more robust and fair when pretrained on uncurated images without supervision P Goyal, Q Duval, I Seessel, M Caron, I Misra, L Sagun, A Joulin, ... arXiv preprint arXiv:2202.08360, 2022 | 51 | 2022 |
| Focal loss for dense object detection. arXiv e-prints TY Lin, P Goyal, R Girshick, K He, P Dollár arXiv preprint arXiv:1708.02002 2 (5), 2017 | 15 | 2017 |
| A self-supervised descriptor for image copy detection E Pizzi, SD Roy, SN Ravindra, P Goyal, M Douze Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 9 | 2022 |
| Fairness indicators for systematic assessments of visual feature extractors P Goyal, AR Soriano, C Hazirbas, L Sagun, N Usunier 2022 ACM Conference on Fairness, Accountability, and Transparency, 70-88, 2022 | 8 | 2022 |
| Peer-to-peer insult detection in online communities P Goyal, GS Kalra IITK Unpubl, 2013 | 6 | 2013 |
| Tensor Iterators for Flexible High-Performance Tensor Computation J Jolly, P Goyal, V Sahoo, H Johansen, M Hall International Workshop on Languages and Compilers for Parallel Computing, 22-28, 2023 | | 2023 |
| Data Leakage: Collusion Graph for determining usage of Beacons and their providers P Goyal Internal technical conference of Yahoo!, 349, 2013 | | 2013 |
Ross GirshickResearch Scientist, Facebook AI Research (FAIR)在 eecs.berkeley.edu 的电子邮件经过验证
