| The apolloscape dataset for autonomous driving X Huang, X Cheng, Q Geng, B Cao, D Zhou, P Wang, Y Lin, R Yang CVPRW 2018, 954-960, 2018 | 393 | 2018 |
| The apolloscape open dataset for autonomous driving and its application X Huang, P Wang, X Cheng, D Zhou, Q Geng, R Yang T-PAMI 2020, 2018 | 351 | 2018 |
| Iou loss for 2d/3d object detection D Zhou, J Fang, X Song, C Guan, J Yin, Y Dai, R Yang 3DV 2019, 85-94, 2019 | 224 | 2019 |
| Apollocar3d: A large 3d car instance understanding benchmark for autonomous driving X Song, P Wang, D Zhou, R Zhu, C Guan, Y Dai, H Su, H Li, R Yang CVPR 2019, 5452-5462, 2019 | 112 | 2019 |
| Lidar-based online 3d video object detection with graph-based message passing and spatiotemporal transformer attention J Yin, J Shen, C Guan, D Zhou, R Yang CVPR 2020, 11495-11504, 2020 | 98 | 2020 |
| Augmented lidar simulator for autonomous driving J Fang, D Zhou, F Yan, T Zhao, F Zhang, Y Ma, L Wang, R Yang RAL 2020 5 (2), 1931-1938, 2020 | 72 | 2020 |
| 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 CVPR 2020, 1839-1849, 2020 | 67 | 2020 |
| Channel attention based iterative residual learning for depth map super-resolution X Song, Y Dai, D Zhou, L Liu, W Li, H Li, R Yang CVPR 2020, 5631-5640, 2020 | 58 | 2020 |
| Reliable scale estimation and correction for monocular visual odometry D Zhou, Y Dai, H Li IV 2016, 490-495, 2016 | 55 | 2016 |
| Autoshape: Real-time shape-aware monocular 3d object detection Z Liu, D Zhou, F Lu, J Fang, L Zhang ICCV 2021, 15641-15650, 2021 | 54 | 2021 |
| Ground-plane-based absolute scale estimation for monocular visual odometry D Zhou, Y Dai, H Li IEEE T-ITS 2019 21 (2), 791-802, 2019 | 41 | 2019 |
| Moving object detection and segmentation in urban environments from a moving platform D Zhou, V Frémont, B Quost, Y Dai, H Li IVC 2017 68, 76-87, 2017 | 39 | 2017 |
| FusionPainting: Multimodal fusion with adaptive attention for 3d object detection S Xu, D Zhou, J Fang, J Yin, Z Bin, L Zhang ITSC 2021, 3047-3054, 2021 | 37 | 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 | 28 | 2018 |
| Dvi: Depth guided video inpainting for autonomous driving M Liao, F Lu, D Zhou, S Zhang, W Li, R Yang ECCV 2020, 1-17, 2020 | 21 | 2020 |
| 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 T-IP 2021 30, 4691-4705, 2021 | 20 | 2021 |
| On modeling ego-motion uncertainty for moving object detection from a mobile platform D Zhou, V Frémont, B Quost, B Wang IV 2014, 1332-1338, 2014 | 18 | 2014 |
| A robust seamless image stitching algorithm based on feature points D Zhou, M He, Q Yang Measurement & Control Technology 28 (6), 32-36, 2009 | 17* | 2009 |
| Accurate extrinsic calibration between monocular camera and sparse 3D lidar points without markers Z Xiao, H Li, D Zhou, Y Dai, B Dai IV 2017, 424-429, 2017 | 15 | 2017 |
| 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 ACCV 2020, 2020 | 14 | 2020 |
Ruigang YangBaidu Research/Professor of Computer Science, University of KentuckyVerified email at cs.uky.edu
