| Towards using count-level weak supervision for crowd counting Y Lei, Y Liu, P Zhang, L Liu Pattern Recognition 109, 107616, 2021 | 113 | 2021 |
| Semi-supervised crowd counting via self-training on surrogate tasks Y Liu, L Liu, P Wang, P Zhang, Y Lei Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020 | 89 | 2020 |
| BSTS: A Weakly-Supervised Method for Semantic Learning of 3D Point Clouds Y Liu, Q Hu, Y Guo IEEE Transactions on Circuits and Systems for Video Technology, 2024 | 15* | 2024 |
| Auto-ORVNet: Orientation-boosted volumetric neural architecture search for 3D shape classification Z Ma, Z Zhou, Y Liu, Y Lei, H Yan IEEE Access 8, 12942-12954, 2019 | 6 | 2019 |
| Panoptic segmentation of 3D point clouds with Gaussian mixture model in outdoor scenes Y Wang, L Wang, Q Hu, Y Liu, Y Zhang, Y Guo Visual Intelligence 2 (1), 10, 2024 | 4 | 2024 |
| Deep mutual learning for visual tracking K Gao, P Zhang, Y Liu, Z Zhou, G Yang, H Lu Proceedings of the ACM turing celebration conference-China, 1-5, 2019 | 3 | 2019 |
| Unified Retrieval and Reranking Paradigm for Aerial-Ground Cross-Source 3D Place Recognition Z Gu, S Ao, M Chen, Y Liu, Y Zhang, Y Guo 2024 International Conference on Digital Image Computing: Techniques and …, 2024 | | 2024 |
| 3D Scene Graph Guided Vision-Language Pre-training H Liu, Y Ma, Y Liu, H Xiao, Y He arXiv preprint arXiv:2411.18666, 2024 | | 2024 |
Lingqiao LiuAssociate Professor at the University of AdelaideCorreu electrònic verificat a adelaide.edu.au