Követés
Professor Javen Qinfeng Shi
Professor Javen Qinfeng Shi
Director for Causal AI Group, University of Adelaide
E-mail megerősítve itt: adelaide.edu.au - Kezdőlap
Cím
Hivatkozott rá
Hivatkozott rá
Év
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
28732015
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
8702020
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
4932014
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
4922017
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
4492015
Real-time visual tracking using compressive sensing
H Li, C Shen, Q Shi
CVPR 2011, 1305-1312, 2011
4382011
Is face recognition really a compressive sensing problem?
Q Shi, A Eriksson, A Van Den Hengel, C Shen
CVPR 2011, 553-560, 2011
3562011
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
3292019
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
2882009
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
2762013
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
2352013
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
2062020
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
1942018
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
1902020
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
1662015
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
1582008
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
1552013
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
1502024
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
1502020
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
1452011
A rendszer jelenleg nem tudja elvégezni a műveletet. Próbálkozzon újra később.
Cikkek 1–20