| Image-based recommendations on styles and substitutes J McAuley, C Targett, Q Shi, A Van Den Hengel Proceedings of the 38th international ACM SIGIR conference on research and …, 2015 | 2879 | 2015 |
| Mot20: A benchmark for multi object tracking in crowded scenes P Dendorfer, H Rezatofighi, A Milan, J Shi, D Cremers, I Reid, S Roth, ... arXiv preprint arXiv:2003.09003, 2020 | 871 | 2020 |
| From motion blur to motion flow: A deep learning solution for removing heterogeneous motion blur D Gong, J Yang, L Liu, Y Zhang, I Reid, C Shen, A Van Den Hengel, Q Shi Proceedings of the IEEE conference on computer vision and pattern …, 2017 | 493 | 2017 |
| Fast supervised hashing with decision trees for high-dimensional data G Lin, C Shen, Q Shi, A Van den Hengel, D Suter Proceedings of the IEEE conference on computer vision and pattern …, 2014 | 493 | 2014 |
| 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 | 449 | 2015 |
| Real-time visual tracking using compressive sensing H Li, C Shen, Q Shi CVPR 2011, 1305-1312, 2011 | 438 | 2011 |
| Is face recognition really a compressive sensing problem? Q Shi, A Eriksson, A Van Den Hengel, C Shen CVPR 2011, 553-560, 2011 | 356 | 2011 |
| Attention-guided network for ghost-free high dynamic range imaging Q Yan, D Gong, Q Shi, A Hengel, C Shen, I Reid, Y Zhang Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 329 | 2019 |
| Hash kernels for structured data. Q Shi, J Petterson, G Dror, J Langford, A Smola, SVN Vishwanathan Journal of Machine Learning Research 10 (11), 2009 | 288 | 2009 |
| Inductive Hashing on Manifolds F Shen, C Shen, Q Shi, A Hengel, Z Tang IEEE Conference on Computer Vision and Pattern Recognition (26th: 2013 …, 2013 | 276 | 2013 |
| Part-based visual tracking with online latent structural learning R Yao, Q Shi, C Shen, Y Zhang, A Van Den Hengel Proceedings of the IEEE conference on computer vision and pattern …, 2013 | 235 | 2013 |
| Deep HDR imaging via a non-local network Q Yan, L Zhang, Y Liu, Y Zhu, J Sun, Q Shi, Y Zhang IEEE Transactions on Image Processing 29, 4308-4322, 2020 | 206 | 2020 |
| Seeing deeply and bidirectionally: A deep learning approach for single image reflection removal J Yang, D Gong, L Liu, Q Shi Proceedings of the european conference on computer vision (ECCV), 654-669, 2018 | 194 | 2018 |
| COVID-19 chest CT image segmentation--a deep convolutional neural network solution Q Yan, B Wang, D Gong, C Luo, W Zhao, J Shen, Q Shi, S Jin, L Zhang, ... arXiv preprint arXiv:2004.10987, 2020 | 191 | 2020 |
| Hashing on nonlinear manifolds F Shen, C Shen, Q Shi, A Van den Hengel, Z Tang, HT Shen IEEE Transactions on Image Processing 24 (6), 1839-1851, 2015 | 166 | 2015 |
| Discriminative human action segmentation and recognition using semi-Markov model Q Shi, L Wang, L Cheng, A Smola 2008 IEEE Conference on Computer Vision and Pattern Recognition, 1-8, 2008 | 158 | 2008 |
| Sensor enabled wearable RFID technology for mitigating the risk of falls near beds RLS Torres, DC Ranasinghe, Q Shi, AP Sample 2013 IEEE international conference on RFID (RFID), 191-198, 2013 | 155 | 2013 |
| A survey on deep neural network pruning: Taxonomy, comparison, analysis, and recommendations H Cheng, M Zhang, JQ Shi IEEE Transactions on Pattern Analysis and Machine Intelligence, 2024 | 150 | 2024 |
| Counterfactual vision and language learning E Abbasnejad, D Teney, A Parvaneh, J Shi, A Hengel Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 150 | 2020 |
| Human action segmentation and recognition using discriminative semi-markov models Q Shi, L Cheng, L Wang, A Smola International journal of computer vision 93, 22-32, 2011 | 145 | 2011 |
Anton van den HengelDirector of the Centre for Augmented Reasoning at AIML.確認したメール アドレス: adelaide.edu.au
