| Deep Learning for 3D Point Clouds: A Survey Y Guo, H Wang, Q Hu, H Liu, L Liu, M Bennamoun IEEE Transactions on Pattern Analysis and Machine Intelligence, 1-27, 2020 | 677 | 2020 |
| 3D Object Recognition in Cluttered Scenes with Local Surface Features: A Survey Y Guo, M Bennamoun, F Sohel, M Lu, J Wan IEEE Transactions on Pattern Analysis and Machine Intelligence 36 (11), 2270 …, 2014 | 592 | 2014 |
| RandLA-Net: Efficient Semantic Segmentation of Large-scale Point Clouds Q Hu, B Yang, L Xie, S Rosa, Y Guo, Z Wang, N Trigoni, A Markham IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), 2020 | 584 | 2020 |
| Rotational Projection Statistics for 3D Local Surface Description and Object Recognition Y Guo, F Sohel, M Bennamoun, M Lu, J Wan International Journal of Computer Vision 105 (1), 63-86, 2013 | 540 | 2013 |
| A Comprehensive Performance Evaluation of 3D Local Feature Descriptors Y Guo, M Bennamoun, F Sohel, M Lu, J Wan, NM Kwok International Journal of Computer Vision 116 (1), 66-89, 2016 | 489 | 2016 |
| Median Robust Extended Local Binary Pattern for Texture Classification L Liu, S Lao, P Fieguth, Y Guo, X Wang, M Pietikainen IEEE Transactions on Image Processing, 2016 | 379 | 2016 |
| Local binary features for texture classification: Taxonomy and experimental study L Liu, P Fieguth, Y Guo, X Wang, M Pietikäinen Pattern Recognition 62, 135-160, 2017 | 343 | 2017 |
| Learning for Disparity Estimation through Feature Constancy Z Liang, Y Feng, Y Guo, H Liu, L Qiao, W Chen, L Zhou, J Zhang Computer Vision and Pattern Recognition (CVPR), IEEE International …, 2018 | 244 | 2018 |
| Learning Parallax Attention for Stereo Image Super-Resolution L Wang, Y Wang, Z Liang, Z Lin, J Yang, W An, Y Guo Computer Vision and Pattern Recognition (CVPR), IEEE International Conference on, 2019 | 151 | 2019 |
| An Accurate and Robust Range Image Registration Algorithm for 3D Object Modeling Y Guo, F Sohel, M Bennamoun, J Wan, M Lu IEEE Transactions on Multimedia 16 (5), 1377-1390, 2014 | 141 | 2014 |
| An Efficient 3D Face Recognition Approach using Local Geometrical Signatures Y Lei, M Bennamoun, M Hayat, Y Guo Pattern Recognition 47 (2), 509-524, 2014 | 131 | 2014 |
| Hyperspectral image restoration using low-rank tensor recovery H Fan, Y Chen, Y Guo, H Zhang, G Kuang IEEE Journal of Selected Topics in Applied Earth Observations and Remote …, 2017 | 113 | 2017 |
| A novel local surface feature for 3D object recognition under clutter and occlusion Y Guo, F Sohel, M Bennamoun, J Wan, M Lu Information Sciences 293, 196-213, 2015 | 103 | 2015 |
| Learning Multi-view Representation with LSTM for 3D Shape Recognition and Retrieval C Ma, Y Guo, J Yang, W An IEEE Transactions on Multimedia, 2018 | 102 | 2018 |
| Spatial-Spectral Total Variation Regularized Low-Rank Tensor Decomposition for Hyperspectral Image Denoising H Fan, C Li, Y Guo, G Kuang, J Ma IEEE Transactions on Geoscience and Remote Sensing, 2018 | 93 | 2018 |
| An Integrated Framework for 3-D Modeling, Object Detection and Pose Estimation From Point-Clouds Y Guo, M Bennamoun, F Sohel, M Lu, J Wan IEEE Transactions on Instrumentation and Measurement 64 (3), 683 - 693, 2015 | 90 | 2015 |
| A Two-Phase Weighted Collaborative Representation for 3D Partial Face Recognition with Single Sample Y Lei, Y Guo, M Hayat, M Bennamoun, X Zhou Pattern Recognition 52 (4), 218-237, 2016 | 83 | 2016 |
| TriSI: A distinctive local surface descriptor for 3D modeling and object recognition Y Guo, F Sohel, M Bennamoun, M Lu, J Wan Computer Graphics Theory and Applications (GRAPP), 8th International …, 2013 | 79 | 2013 |
| Towards real-time 3D object recognition: A lightweight volumetric CNN framework using multitask learning S Zhi, Y Liu, X Li, Y Guo Computers & Graphics, 2017 | 78 | 2017 |
| Unsupervised Degradation Representation Learning for Blind Super-Resolution L Wang, Y Wang, X Dong, Q Xu, J Yang, W An, Y Guo International Conference on Computer Vision and Pattern Recognition (CVPR), 2021 | 75 | 2021 |
Mohammed BennamounThe University of Western AustraliaVerified email at uwa.edu.au
