| Few-shot image recognition by predicting parameters from activations S Qiao, C Liu, W Shen, AL Yuille Proceedings of the IEEE conference on computer vision and pattern …, 2018 | 514 | 2018 |
| Detectors: Detecting objects with recursive feature pyramid and switchable atrous convolution S Qiao, LC Chen, A Yuille Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021 | 396 | 2021 |
| Deep Co-Training for Semi-Supervised Image Recognition S Qiao, W Shen, Z Zhang, B Wang, A Yuille The European Conference on Computer Vision (ECCV), 2018 | 312 | 2018 |
| Single-shot object detection with enriched semantics Z Zhang, S Qiao, C Xie, W Shen, B Wang, AL Yuille Proceedings of the IEEE conference on computer vision and pattern …, 2018 | 209 | 2018 |
| Micro-batch training with batch-channel normalization and weight standardization S Qiao, H Wang, C Liu, W Shen, A Yuille arXiv preprint arXiv:1903.10520, 2019 | 205 | 2019 |
| Unrealcv: Virtual worlds for computer vision W Qiu, F Zhong, Y Zhang, S Qiao, Z Xiao, TS Kim, Y Wang Proceedings of the 25th ACM international conference on Multimedia, 1221-1224, 2017 | 181 | 2017 |
| Training Deep Neural Networks in Generations: A More Tolerant Teacher Educates Better Students C Yang, L Xie, S Qiao, A Yuille Proceedings of the AAAI Conference on Artificial Intelligence, 2019 | 165* | 2019 |
| Vip-deeplab: Learning visual perception with depth-aware video panoptic segmentation S Qiao, Y Zhu, H Adam, A Yuille, LC Chen Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 77 | 2021 |
| Sort: Second-order response transform for visual recognition Y Wang, L Xie, C Liu, S Qiao, Y Zhang, W Zhang, Q Tian, A Yuille Proceedings of the IEEE International Conference on Computer Vision, 1359-1368, 2017 | 58 | 2017 |
| Scalenet: Guiding object proposal generation in supermarkets and beyond S Qiao, W Shen, W Qiu, C Liu, A Yuille Proceedings of the IEEE International Conference on Computer Vision, 1791-1800, 2017 | 48 | 2017 |
| Robust face detection via learning small faces on hard images Z Zhang, W Shen, S Qiao, Y Wang, B Wang, A Yuille Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2020 | 38 | 2020 |
| Scaling wide residual networks for panoptic segmentation LC Chen, H Wang, S Qiao arXiv preprint arXiv:2011.11675, 2020 | 26 | 2020 |
| Neural rejuvenation: Improving deep network training by enhancing computational resource utilization S Qiao, Z Lin, J Zhang, AL Yuille Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 24 | 2019 |
| DetectoRS: Detecting objects with recursive feature pyramid and switchable atrous convolution. arXiv 2020 S Qiao, LC Chen, A Yuille arXiv preprint arXiv:2006.02334, 2020 | 18 | 2020 |
| Deeply shape-guided cascade for instance segmentation H Ding, S Qiao, A Yuille, W Shen Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 16* | 2021 |
| Multi-Scale Spatially-Asymmetric Recalibration for Image Classification Y Wang, L Xie, S Qiao, Y Zhang, W Zhang, AL Yuille The European Conference on Computer Vision (ECCV), 2018 | 16 | 2018 |
| Tdapnet: Prototype network with recurrent top-down attention for robust object classification under partial occlusion M Xiao, A Kortylewski, R Wu, S Qiao, W Shen, A Yuille arXiv preprint arXiv:1909.03879, 2019 | 15 | 2019 |
| Deeplab2: A tensorflow library for deep labeling M Weber, H Wang, S Qiao, J Xie, MD Collins, Y Zhu, L Yuan, D Kim, Q Yu, ... arXiv preprint arXiv:2106.09748, 2021 | 14 | 2021 |
| Cmt-deeplab: Clustering mask transformers for panoptic segmentation Q Yu, H Wang, D Kim, S Qiao, M Collins, Y Zhu, H Adam, A Yuille, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 12 | 2022 |
| Rethinking normalization and elimination singularity in neural networks S Qiao, H Wang, C Liu, W Shen, A Yuille arXiv preprint arXiv:1911.09738, 2019 | 12 | 2019 |
Alan YuilleProfessor of Cognitive Science and Computer Science, Johns Hopkins UniversityΗ διεύθυνση ηλεκτρονικού ταχυδρομείου έχει επαληθευτεί στον τομέα jhu.edu
