| 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 | 8594 | 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 | 937 | 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 | 590 | 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 | 241 | 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 | 211 | 2024 |
| 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 | 169 | 2018 |
| 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 | 164 | 2019 |
| Seed1. 5-vl technical report D Guo, F Wu, F Zhu, F Leng, G Shi, H Chen, H Fan, J Wang, J Jiang, ... arXiv preprint arXiv:2505.07062, 2025 | 150 | 2025 |
| 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 | 128 | 2019 |
| Seed1. 5-thinking: Advancing superb reasoning models with reinforcement learning BD Seed, J Chen, T Fan, X Liu, L Liu, Z Lin, M Wang, C Wang, X Wei, ... arXiv preprint arXiv:2504.13914, 2025 | 116 | 2025 |
| Copilot4d: 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 | 105 | 2023 |
| Collaborative deep ranking: A hybrid pair-wise recommendation algorithm with implicit feedback H Ying, L Chen, Y Xiong, J Wu Pacific-asia conference on knowledge discovery and data mining, 555-567, 2016 | 102 | 2016 |
| 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 | 100 | 2019 |
| 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 | 93 | 2020 |
| Loco: Local contrastive representation learning Y Xiong, M Ren, R Urtasun Advances in neural information processing systems 33, 11142-11153, 2020 | 86 | 2020 |
| Ultralidar: Learning compact representations for lidar completion and generation Y Xiong, WC Ma, J Wang, R Urtasun arXiv preprint arXiv:2311.01448, 2023 | 81* | 2023 |
| Weakly-supervised 3d shape completion in the wild J Gu, WC Ma, S Manivasagam, W Zeng, Z Wang, Y Xiong, H Su, ... European conference on computer vision, 283-299, 2020 | 72 | 2020 |
| 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 | 71 | 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 | 60 | 2023 |
| 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 | 51 | 2021 |
Raquel UrtasunFounder & CEO Waabi, Professor, University of Toronto.Verified email at cs.toronto.edu
