| Joint probabilistic data association revisited SH Rezatofighi, A Milan, Z Zhang, Q Shi, A Dick, I Reid Proceedings of the IEEE international conference on computer vision, 3047-3055, 2015 | 450 | 2015 |
| Convolutional sequence to sequence model for human dynamics C Li, Z Zhang, WS Lee, GH Lee Proceedings of the IEEE conference on computer vision and pattern …, 2018 | 395 | 2018 |
| Learning deep gradient descent optimization for image deconvolution D Gong, Z Zhang, Q Shi, A Van Den Hengel, C Shen, Y Zhang IEEE transactions on neural networks and learning systems 31 (12), 5468-5482, 2020 | 136* | 2020 |
| Deep Graphical Feature Learning for the Feature Matching Problem Z Zhang, WS Lee IEEE International Conference on Computer Vision, 2019 | 86 | 2019 |
| Pairwise Matching through Max-Weight Bipartite Belief Propagation Z Zhang, Q Shi, J McAuley, W Wei, Y Zhang, A Van Den Hengel IEEE Conference on Computer Vision and Pattern Recognition, 2016 | 64 | 2016 |
| Factor graph neural networks Z Zhang, F Wu, WS Lee Advances in Neural Information Processing Systems 33, 8577-8587, 2020 | 63 | 2020 |
| Learning graph structure for multi-label image classification via clique generation M Tan, Q Shi, A van den Hengel, C Shen, J Gao, F Hu, Z Zhang Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2015 | 63 | 2015 |
| Real-time correlation filter tracking by efficient dense belief propagation with structure preserving R Yao, S Xia, Z Zhang, Y Zhang IEEE Transactions on Multimedia 19 (4), 772-784, 2016 | 45 | 2016 |
| NTIRE 2022 challenge on high dynamic range imaging: Methods and results E Pérez-Pellitero, S Catley-Chandar, R Shaw, A Leonardis, R Timofte, ... Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022 | 43 | 2022 |
| Joint Probabilistic Matching Using m-Best Solutions SH Rezatofighi, A Milan, Z Zhang, Q Shi, A Dick, I Reid IEEE Conference on Computer Vision and Pattern Recognition, 2016 | 41 | 2016 |
| A bidirectional graph neural network for traveling salesman problems on arbitrary symmetric graphs Y Hu, Z Zhang, Y Yao, X Huyan, X Zhou, WS Lee Engineering Applications of Artificial Intelligence 97, 104061, 2021 | 37 | 2021 |
| Rapid non-destructive method to phenotype stomatal traits P Pathoumthong, Z Zhang, SJ Roy, A El Habti Plant Methods 19 (1), 36, 2023 | 30 | 2023 |
| Truncated matrix power iteration for differentiable DAG learning Z Zhang, I Ng, D Gong, Y Liu, E Abbasnejad, M Gong, K Zhang, JQ Shi Advances in Neural Information Processing Systems 35, 18390-18402, 2022 | 27 | 2022 |
| Identifying weight-variant latent causal models Y Liu, Z Zhang, D Gong, M Gong, B Huang, A Hengel, K Zhang, JQ Shi arXiv preprint arXiv:2208.14153, 2022 | 24 | 2022 |
| SharpFormer: Learning local feature preserving global representations for image deblurring Q Yan, D Gong, P Wang, Z Zhang, Y Zhang, JQ Shi IEEE Transactions on Image Processing 32, 2857-2866, 2023 | 21 | 2023 |
| A lightweight network for high dynamic range imaging Q Yan, S Zhang, W Chen, Y Liu, Z Zhang, Y Zhang, JQ Shi, D Gong Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 16 | 2022 |
| Memory-augmented dynamic neural relational inference D Gong, FZ Zhang, JQ Shi, A Van Den Hengel Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 13 | 2021 |
| Variable kernel density estimation based robust regression and its applications Z Zhang, Y Zhang Neurocomputing 134, 30-37, 2014 | 12 | 2014 |
| Identifiable latent polynomial causal models through the lens of change Y Liu, Z Zhang, D Gong, M Gong, B Huang, A Hengel, K Zhang, JQ Shi arXiv preprint arXiv:2310.15580, 2023 | 11 | 2023 |
| An adaptive markov random field for structured compressive sensing S Suwanwimolkul, L Zhang, D Gong, Z Zhang, C Chen, DC Ranasinghe, ... IEEE Transactions on Image Processing 28 (3), 1556-1570, 2018 | 10 | 2018 |
Professor Javen Qinfeng ShiDirector for Causal AI Group, University of Adelaide確認したメール アドレス: adelaide.edu.au