| Encoder-decoder with atrous separable convolution for semantic image segmentation LC Chen, Y Zhu, G Papandreou, F Schroff, H Adam Proceedings of the European conference on computer vision (ECCV), 801-818, 2018 | 4016 | 2018 |
| Skip-thought vectors R Kiros, Y Zhu, RR Salakhutdinov, R Zemel, R Urtasun, A Torralba, ... Advances in neural information processing systems, 3294-3302, 2015 | 2221 | 2015 |
| Aligning books and movies: Towards story-like visual explanations by watching movies and reading books Y Zhu, R Kiros, R Zemel, R Salakhutdinov, R Urtasun, A Torralba, S Fidler Proceedings of the IEEE international conference on computer vision, 19-27, 2015 | 1132 | 2015 |
| Searching for mobilenetv3 A Howard, M Sandler, G Chu, LC Chen, B Chen, M Tan, W Wang, Y Zhu, ... Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 1004 | 2019 |
| 3d object proposals for accurate object class detection X Chen, K Kundu, Y Zhu, AG Berneshawi, H Ma, S Fidler, R Urtasun Advances in Neural Information Processing Systems, 424-432, 2015 | 590 | 2015 |
| Movieqa: Understanding stories in movies through question-answering M Tapaswi, Y Zhu, R Stiefelhagen, A Torralba, R Urtasun, S Fidler Proceedings of the IEEE conference on computer vision and pattern …, 2016 | 425 | 2016 |
| Searching for efficient multi-scale architectures for dense image prediction LC Chen, MD Collins, Y Zhu, G Papandreou, B Zoph, F Schroff, H Adam, ... arXiv preprint arXiv:1809.04184, 2018 | 248 | 2018 |
| Spatially adaptive computation time for residual networks M Figurnov, MD Collins, Y Zhu, L Zhang, J Huang, D Vetrov, ... Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2017 | 219 | 2017 |
| 3d object proposals using stereo imagery for accurate object class detection X Chen, K Kundu, Y Zhu, H Ma, S Fidler, R Urtasun IEEE transactions on pattern analysis and machine intelligence 40 (5), 1259-1272, 2017 | 210 | 2017 |
| segdeepm: Exploiting segmentation and context in deep neural networks for object detection Y Zhu, R Urtasun, R Salakhutdinov, S Fidler Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2015 | 171 | 2015 |
| Axial-deeplab: Stand-alone axial-attention for panoptic segmentation H Wang, Y Zhu, B Green, H Adam, A Yuille, LC Chen European Conference on Computer Vision, 108-126, 2020 | 94 | 2020 |
| Panoptic-deeplab: A simple, strong, and fast baseline for bottom-up panoptic segmentation B Cheng, MD Collins, Y Zhu, T Liu, TS Huang, H Adam, LC Chen Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 86 | 2020 |
| Deeperlab: Single-shot image parser TJ Yang, MD Collins, Y Zhu, JJ Hwang, T Liu, X Zhang, V Sze, ... arXiv preprint arXiv:1902.05093, 2019 | 82 | 2019 |
| Spgnet: Semantic prediction guidance for scene parsing B Cheng, LC Chen, Y Wei, Y Zhu, Z Huang, J Xiong, TS Huang, WM Hwu, ... Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 53 | 2019 |
| Max-deeplab: End-to-end panoptic segmentation with mask transformers H Wang, Y Zhu, H Adam, A Yuille, LC Chen Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 34 | 2021 |
| Panoptic-deeplab B Cheng, MD Collins, Y Zhu, T Liu, TS Huang, H Adam, LC Chen arXiv preprint arXiv:1910.04751, 2019 | 30 | 2019 |
| Search to distill: Pearls are everywhere but not the eyes Y Liu, X Jia, M Tan, R Vemulapalli, Y Zhu, B Green, X Wang Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 27 | 2020 |
| Contextual object detection with spatial context prototypes Y Zhu, J Zhu, R Zhang IEEE Transactions on Multimedia 16 (6), 1585-1596, 2014 | 8 | 2014 |
| 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 | 7 | 2021 |
| Discovering spatial context prototypes for object detection Y Zhu, J Zhu, R Zhang 2013 IEEE International Conference on Multimedia and Expo (ICME), 1-6, 2013 | 4 | 2013 |
Sanja FidlerUniversity of Toronto, NVIDIAVerified email at cs.toronto.edu
