| Lq-nets: Learned quantization for highly accurate and compact deep neural networks D Zhang, J Yang, D Ye, G Hua Proceedings of the European conference on computer vision (ECCV), 365-382, 2018 | 772 | 2018 |
| Lidarmultinet: Towards a unified multi-task network for lidar perception D Ye, Z Zhou, W Chen, Y Xie, Y Wang, P Wang, H Foroosh AAAI 2023, 2022 | 56 | 2022 |
| LidarMultiNet: Unifying LiDAR Semantic Segmentation, 3D Object Detection, and Panoptic Segmentation in a Single Multi-task Network D Ye, W Chen, Z Zhou, Y Xie, Y Wang, P Wang, H Foroosh arXiv:2206.11428, 2022 | 9 | 2022 |
| Lpformer: Lidar pose estimation transformer with multi-task network D Ye, Y Xie, W Chen, Z Zhou, H Foroosh ICRA 2024, 2023 | 4 | 2023 |
| LiDARFormer: A Unified Transformer-based Multi-task Network for LiDAR Perception Z Zhou, D Ye, W Chen, Y Xie, Y Wang, P Wang, H Foroosh ICRA 2024, 2023 | 2 | 2023 |
| Autonomous driving lidar technology P Wang, W Yu, X Zhao, D Ye US Patent US20230182774A1, 2023 | | 2023 |
| Quantification for machine learning models D Zhang, J Yang, G Hua, D Ye CN Patent CN110,728,350 A, 2020 | | 2020 |
