| Focal Loss for Dense Object Detection TY Lin, P Goyal, R Girshick, K He, P Dollįr arXiv preprint arXiv:1708.02002, 2017 | 33297 | 2017 |
| Accurate, Large Minibatch SGD: Training ImageNet in 1 Hour P Goyal, P Dollįr, R Girshick, P Noordhuis, L Wesolowski, A Kyrola, ... https://arxiv.org/abs/1706.02677, 2017 | 4092 | 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 | 4060 | 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 | 498 | 2018 |
| Scaling and Benchmarking Self-Supervised Visual Representation Learning P Goyal, D Mahajan, A Gupta, I Misra https://arxiv.org/abs/1905.01235, 2019 | 476 | 2019 |
| P. Doll ar,“Focal loss for dense object detection,” TY Lin, P Goyal, R Girshick, K He Proc. IEEE Int. Conf. Comput. Vis, 2980-2988, 2017 | 414 | 2017 |
| 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 | 268 | 2021 |
| Focal loss for dense object detection. arXiv 2017 TY Lin, P Goyal, R Girshick, K He, P Dollįr arXiv preprint arXiv:1708.02002, 2002 | 158 | 2002 |
| Accurate, large minibatch sgd: Training imagenet in 1 hour. arXiv 2017 P Goyal, P Dollįr, R Girshick, P Noordhuis, L Wesolowski, A Kyrola, ... arXiv preprint arXiv:1706.02677, 2019 | 150 | 2019 |
| Focal loss for dense object detection. 2017 TY Lin, P Goyal, R Girshick, K He, P Dollįr arXiv preprint arXiv:1708.02002, 2022 | 121 | 2022 |
| 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 | 113 | 2022 |
| Focal loss for dense object detection. arXiv TY Lin, P Goyal, R Girshick, K He, P Dollįr arXiv preprint arXiv:1708.02002, 2017 | 110 | 2017 |
| VISSL P Goyal, B Lefaudeux, M Singh, J Reizenstein, V Reis, M Xu, M Leavitt, ... | 90 | 2021 |
| 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 | 68 | 2019 |
| 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 | 67 | 2022 |
| 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 | 67 | 2017 |
| Focal loss for dense object detection. CoRR abs/1708.02002 (2017) T Lin, P Goyal, RB Girshick, K He, P Dollįr arXiv preprint arXiv:1708.02002, 2017 | 65 | 2017 |
| Piotr Doll ́ar TY Lin, P Goyal, R Girshick, K He Ross B Girshick, KaimingHe, Bharath Hariharan, and Serge J Belongie …, 2017 | 63 | 2017 |
| Focal loss for dense object detection, IEEE Int TY Lin, P Goyal, R Girshick, K He, P Dollįr Conf. on Computer Vision, 2017 | 59 | 2017 |
| Fairness indicators for systematic assessments of visual feature extractors P Goyal, AR Soriano, C Hazirbas, L Sagun, N Usunier Proceedings of the 2022 ACM Conference on Fairness, Accountability, and …, 2022 | 27 | 2022 |
Tsung-Yi LinResearch Scientist, NVIDIAEmail verificata su nvidia.com
