| Deformable convolutional networks J Dai, H Qi, Y Xiong, Y Li, G Zhang, H Hu, Y Wei Proceedings of the IEEE international conference on computer vision, 764-773, 2017 | 7117 | 2017 |
| Deep feature flow for video recognition X Zhu, Y Xiong, J Dai, L Yuan, Y Wei Proceedings of the IEEE conference on computer vision and pattern …, 2017 | 870 | 2017 |
| Upsnet: A unified panoptic segmentation network Y Xiong, R Liao, H Zhao, R Hu, M Bai, E Yumer, R Urtasun Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 529 | 2019 |
| Polytransform: Deep polygon transformer for instance segmentation J Liang, N Homayounfar, WC Ma, Y Xiong, R Hu, R Urtasun Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 205 | 2020 |
| Deep rigid instance scene flow WC Ma, S Wang, R Hu, Y Xiong, R Urtasun Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 154 | 2019 |
| Reviving and improving recurrent back-propagation R Liao, Y Xiong, E Fetaya, L Zhang, KJ Yoon, X Pitkow, R Urtasun, ... International Conference on Machine Learning, 3082-3091, 2018 | 147 | 2018 |
| Inference in probabilistic graphical models by graph neural networks KJ Yoon, R Liao, Y Xiong, L Zhang, E Fetaya, R Urtasun, R Zemel, ... 2019 53rd Asilomar Conference on Signals, Systems, and Computers, 868-875, 2019 | 120 | 2019 |
| Dmm-net: Differentiable mask-matching network for video object segmentation X Zeng, R Liao, L Gu, Y Xiong, S Fidler, R Urtasun Proceedings of the IEEE/CVF international conference on computer vision …, 2019 | 98 | 2019 |
| Collaborative deep ranking: A hybrid pair-wise recommendation algorithm with implicit feedback H Ying, L Chen, Y Xiong, J Wu Advances in Knowledge Discovery and Data Mining: 20th Pacific-Asia …, 2016 | 96 | 2016 |
| Discrete residual flow for probabilistic pedestrian behavior prediction A Jain, S Casas, R Liao, Y Xiong, S Feng, S Segal, R Urtasun Conference on Robot Learning, 407-419, 2020 | 83 | 2020 |
| Loco: Local contrastive representation learning Y Xiong, M Ren, R Urtasun Advances in neural information processing systems 33, 11142-11153, 2020 | 77 | 2020 |
| Weakly-supervised 3d shape completion in the wild J Gu, WC Ma, S Manivasagam, W Zeng, Z Wang, Y Xiong, H Su, ... Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020 | 62 | 2020 |
| Efficient deformable convnets: Rethinking dynamic and sparse operator for vision applications Y Xiong, Z Li, Y Chen, F Wang, X Zhu, J Luo, W Wang, T Lu, H Li, Y Qiao, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024 | 54 | 2024 |
| Self-supervised representation learning from flow equivariance Y Xiong, M Ren, W Zeng, R Urtasun Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 46 | 2021 |
| Learning unsupervised world models for autonomous driving via discrete diffusion L Zhang, Y Xiong, Z Yang, S Casas, R Hu, R Urtasun arXiv preprint arXiv:2311.01017, 2023 | 42 | 2023 |
| Ultralidar: Learning compact representations for lidar completion and generation Y Xiong, WC Ma, J Wang, R Urtasun arXiv preprint arXiv:2311.01448, 2023 | 42* | 2023 |
| Mm-interleaved: Interleaved image-text generative modeling via multi-modal feature synchronizer C Tian, X Zhu, Y Xiong, W Wang, Z Chen, W Wang, Y Chen, L Lu, T Lu, ... arXiv preprint arXiv:2401.10208, 2024 | 36 | 2024 |
| Towards unsupervised object detection from lidar point clouds L Zhang, AJ Yang, Y Xiong, S Casas, B Yang, M Ren, R Urtasun Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 33 | 2023 |
| Levelset r-cnn: A deep variational method for instance segmentation N Homayounfar, Y Xiong, J Liang, WC Ma, R Urtasun Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020 | 33 | 2020 |
| Rethinking closed-loop training for autonomous driving C Zhang, R Guo, W Zeng, Y Xiong, B Dai, R Hu, M Ren, R Urtasun European Conference on Computer Vision, 264-282, 2022 | 29 | 2022 |
Raquel UrtasunFounder & CEO Waabi, Professor, University of Toronto.E-mail megerősítve itt: cs.toronto.edu
