| Iou loss for 2d/3d object detection D Zhou, J Fang, X Song, C Guan, J Yin, Y Dai, R Yang 2019 international conference on 3D vision (3DV), 85-94, 2019 | 421 | 2019 |
| Invisible for both camera and lidar: Security of multi-sensor fusion based perception in autonomous driving under physical-world attacks Y Cao, N Wang, C Xiao, D Yang, J Fang, R Yang, QA Chen, M Liu, B Li 2021 IEEE symposium on security and privacy (SP), 176-194, 2021 | 190 | 2021 |
| AADS: Augmented autonomous driving simulation using data-driven algorithms W Li, CW Pan, R Zhang, JP Ren, YX Ma, J Fang, FL Yan, QC Geng, ... Science robotics 4 (28), eaaw0863, 2019 | 177 | 2019 |
| Deep fusionnet for point cloud semantic segmentation F Zhang, J Fang, B Wah, P Torr Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020 | 175 | 2020 |
| Adversarial objects against lidar-based autonomous driving systems Y Cao, C Xiao, D Yang, J Fang, R Yang, M Liu, B Li arXiv preprint arXiv:1907.05418, 2019 | 166 | 2019 |
| Fusionpainting: Multimodal fusion with adaptive attention for 3d object detection S Xu, D Zhou, J Fang, J Yin, Z Bin, L Zhang 2021 IEEE International Intelligent Transportation Systems Conference (ITSC …, 2021 | 136 | 2021 |
| Augmented LiDAR simulator for autonomous driving J Fang, D Zhou, F Yan, T Zhao, F Zhang, Y Ma, L Wang, R Yang IEEE Robotics and Automation Letters 5 (2), 1931-1938, 2020 | 128 | 2020 |
| Autoshape: Real-time shape-aware monocular 3d object detection Z Liu, D Zhou, F Lu, J Fang, L Zhang Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 126 | 2021 |
| Joint 3d instance segmentation and object detection for autonomous driving D Zhou, J Fang, X Song, L Liu, J Yin, Y Dai, H Li, R Yang Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 115 | 2020 |
| ProposalContrast: Unsupervised Pre-training for LiDAR-Based 3D Object Detection J Yin, D Zhou, L Zhang, J Fang, CZ Xu, J Shen, W Wang European conference on computer vision, 17-33, 2022 | 91 | 2022 |
| Semi-supervised 3D object detection with proficient teachers J Yin, J Fang, D Zhou, L Zhang, CZ Xu, J Shen, W Wang European Conference on Computer Vision, 727-743, 2022 | 65 | 2022 |
| Instance segmentation of lidar point clouds F Zhang, C Guan, J Fang, S Bai, R Yang, PHS Torr, V Prisacariu 2020 IEEE International Conference on Robotics and Automation (ICRA), 9448-9455, 2020 | 58 | 2020 |
| Lidar-aug: A general rendering-based augmentation framework for 3d object detection J Fang, X Zuo, D Zhou, S Jin, S Wang, L Zhang Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 50 | 2021 |
| MLDA-Net: Multi-level dual attention-based network for self-supervised monocular depth estimation X Song, W Li, D Zhou, Y Dai, J Fang, H Li, L Zhang IEEE Transactions on Image Processing 30, 4691-4705, 2021 | 42 | 2021 |
| Simulating LIDAR point cloud for autonomous driving using real-world scenes and traffic flows J Fang, F Yan, T Zhao, F Zhang, D Zhou, R Yang, Y Ma, L Wang arXiv preprint arXiv:1811.07112 1, 2018 | 40 | 2018 |
| MapFusion: A General Framework for 3D Object Detection with HDMaps J Fang, D Zhou, X Song, L Zhang IROS 2021, 2021 | 23 | 2021 |
| Large Scale Autonomous Driving Scenarios Clustering with Self-supervised Feature Extraction J Zhao, J Fang, Z Ye, L Zhang IV 2021, 2021 | 19 | 2021 |
| Rotpredictor: Unsupervised canonical viewpoint learning for point cloud classification J Fang, D Zhou, X Song, S Jin, R Yang, L Zhang 2020 International Conference on 3D Vision (3DV), 987-996, 2020 | 17 | 2020 |
| Iafa: Instance-aware feature aggregation for 3d object detection from a single image D Zhou, X Song, Y Dai, J Yin, F Lu, M Liao, J Fang, L Zhang Proceedings of the Asian Conference on Computer Vision, 2020 | 15 | 2020 |
| Autoremover: Automatic object removal for autonomous driving videos R Zhang, W Li, P Wang, C Guan, J Fang, Y Song, J Yu, B Chen, W Xu, ... Proceedings of the AAAI Conference on Artificial Intelligence 34 (07), 12853 …, 2020 | 13 | 2020 |
Ruigang YangBaidu Research/Professor of Computer Science, University of Kentucky在 cs.uky.edu 的电子邮件经过验证
