| RGCNN: Regularized Graph CNN for Point Cloud Segmentation G Te, W Hu, Z Guo, A Zheng ACM Multimedia, 2018 | 231 | 2018 |
| Multi-resolution Graph Fourier Transform for Compression of Piecewise Smooth Images W Hu, G Cheung, A Ortega, OC Au Transactions on Image Processing 24 (1), 419-433, 2015 | 195 | 2015 |
| Optimized skeleton-based action recognition via sparsified graph regression X Gao, W Hu, J Tang, J Liu, Z Guo Proceedings of the 27th ACM International Conference on Multimedia, 601-610, 2019 | 171* | 2019 |
| Diffusion probabilistic models for 3d point cloud generation S Luo, W Hu Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 114 | 2021 |
| Depth map denoising using graph-based transform and group sparsity W Hu, X Li, G Cheung, O Au 2013 IEEE 15th international workshop on multimedia signal processing (MMSP …, 2013 | 99 | 2013 |
| Multiscale geographically and temporally weighted regression: Exploring the spatiotemporal determinants of housing prices C Wu, F Ren, W Hu, Q Du International Journal of Geographical Information Science 33 (3), 489-511, 2019 | 79 | 2019 |
| Adco: Adversarial contrast for efficient learning of unsupervised representations from self-trained negative adversaries Q Hu, X Wang, W Hu, GJ Qi Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 78 | 2021 |
| Intra-Prediction and Generalized Graph Fourier Transform for Image Coding W Hu, G Cheung, A Ortega IEEE Signal Processing Letters 22 (11), 1913 - 1917, 2015 | 73 | 2015 |
| Depth map compression using multi-resolution graph-based transform for depth-image-based rendering W Hu, G Cheung, X Li, O Au 2012 19th IEEE International Conference on Image Processing, 1297-1300, 2012 | 65 | 2012 |
| Feature Graph Learning for 3D Point Cloud Denoising W Hu, X Gao, G Cheung, Z Guo Transactions on Signal Processing, 2020 | 57 | 2020 |
| Graph-based Dequantization of Block-Compressed Piecewise Smooth Images MK Wei Hu, Gene Cheung IEEE Signal Processing Letters 23 (2), 242-246, 2016 | 51* | 2016 |
| Non-local graph convolutional networks for skeleton-based action recognition L Shi, Y Zhang, J Cheng, H Lu arXiv preprint arXiv:1805.07694 1 (2), 3, 2018 | 45 | 2018 |
| Local frequency interpretation and non-local self-similarity on graph for point cloud inpainting W Hu, Z Fu, Z Guo IEEE Transactions on Image Processing 28 (8), 4087-4100, 2019 | 44 | 2019 |
| Differentiable manifold reconstruction for point cloud denoising S Luo, W Hu Proceedings of the 28th ACM international conference on multimedia, 1330-1338, 2020 | 43 | 2020 |
| Doped phosphorene for hydrogen capture: A DFT study H Zhang, W Hu, A Du, X Lu, Y Zhang, J Zhou, X Lin, Y Tang Applied Surface Science 433, 249-255, 2018 | 42 | 2018 |
| Nonlinear plasmonic frequency conversion through quasiphase matching Z Wu, X Hu, Z Yu, W Hu, F Xu, Y Lu Physical Review B 82 (15), 155107, 2010 | 39 | 2010 |
| Personal photo album compression and management R Zou, OC Au, G Zhou, W Dai, W Hu, P Wan 2013 IEEE International Symposium on Circuits and Systems (ISCAS), 1428-1431, 2013 | 38 | 2013 |
| GraphTER: Unsupervised Learning of Graph Transformation Equivariant Representations via Auto-Encoding Node-wise Transformations X Gao, W Hu, GJ Qi IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020 | 36 | 2020 |
| Score-based point cloud denoising S Luo, W Hu Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 34 | 2021 |
| Edge-aware graph representation learning and reasoning for face parsing G Te, Y Liu, W Hu, H Shi, T Mei Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020 | 33 | 2020 |
Gene CheungProfessor, Department of EECS, York UniversityZweryfikowany adres z yorku.ca
