| Light field image processing: An overview G Wu, B Masia, A Jarabo, Y Zhang, L Wang, Q Dai, T Chai, Y Liu IEEE Journal of Selected Topics in Signal Processing 11 (7), 926-954, 2017 | 589 | 2017 |
| Light field reconstruction using deep convolutional network on EPI G Wu, M Zhao, L Wang, Q Dai, T Chai, Y Liu Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2017 | 236 | 2017 |
| Disentangling light fields for super-resolution and disparity estimation Y Wang, L Wang, G Wu, J Yang, W An, J Yu, Y Guo IEEE Transactions on Pattern Analysis and Machine Intelligence 45 (1), 425-443, 2022 | 183 | 2022 |
| Light field reconstruction using convolutional network on EPI and extended applications G Wu, Y Liu, L Fang, Q Dai, T Chai IEEE transactions on pattern analysis and machine intelligence 41 (7), 1681-1694, 2018 | 131 | 2018 |
| Learning sheared EPI structure for light field reconstruction G Wu, Y Liu, Q Dai, T Chai IEEE Transactions on Image Processing 28 (7), 3261-3273, 2019 | 119 | 2019 |
| Revisiting light field rendering with deep anti-aliasing neural network G Wu, Y Liu, L Fang, T Chai IEEE Transactions on Pattern Analysis and Machine Intelligence 44 (9), 5430-5444, 2021 | 66* | 2021 |
| Spatial-angular attention network for light field reconstruction G Wu, Y Wang, Y Liu, L Fang, T Chai IEEE Transactions on Image Processing 30, 8999-9013, 2021 | 46 | 2021 |
| LocalTrans: A Multiscale Local Transformer Network for Cross-Resolution Homography Estimation R Shao, G Wu, Y Zhou, Y Fu, L Fang, Y Liu Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), 2021 | 39 | 2021 |
| Cross-scale reference-based light field super-resolution M Zhao, G Wu, Y Li, X Hao, L Fang, Y Liu IEEE Transactions on Computational Imaging 4 (3), 406-418, 2018 | 29 | 2018 |
| Cross-MPI: Cross-scale stereo for image superresolution using multiplane images Y Zhou, G Wu, Y Fu, K Li, Y Liu Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 28 | 2021 |
| Real time power equipment meter recognition based on deep learning Z Fan, L Shi, C Xi, H Wang, S Wang, G Wu IEEE Transactions on Instrumentation and Measurement 71, 1-15, 2022 | 27 | 2022 |
| 基于时序图像深度学习的电熔镁炉异常工况诊断 吴高昌， 刘强， 柴天佑， 秦泗钊 自动化学报 45 (8), 1475-1485, 2019 | 13 | 2019 |
| Data mining based noise diagnosis and fuzzy filter design for image processing Y Wang, G Wu, GS Chen, T Chai Computers & Electrical Engineering 40 (7), 2038-2049, 2014 | 13 | 2014 |
| Lfnat 2023 challenge on light field depth estimation: Methods and results H Sheng, Y Liu, J Yu, G Wu, W Xiong, R Cong, R Chen, L Guo, Y Xie, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 12 | 2023 |
| Disturbance robust abnormality diagnosis of fused magnesium furnaces using deep neural networks Q Liu, Y Zhang, G Wu, Z Fan IEEE Transactions on Artificial Intelligence 4 (4), 669-678, 2022 | 8 | 2022 |
| Modeling and control for PEMFC hydrogen management subsystem based on neural network compensation and prescribed tracking accuracy Y Wang, G Wu, Y Wang Fuel 352, 129019, 2023 | 6 | 2023 |
| Joint view synthesis and disparity refinement for stereo matching G Wu, Y Li, Y Huang, Y Liu Frontiers of Computer Science 13, 1337-1352, 2019 | 6 | 2019 |
| Boosting single image super-resolution learnt from implicit multi-image prior D Jin, M Ji, L Xu, G Wu, L Wang, L Fang IEEE Transactions on Image Processing 30, 3240-3251, 2021 | 3 | 2021 |
| How depth estimation in light fields can benefit from super-resolution? M Zhao, G Wu, Y Liu, X Hao International Journal of Advanced Robotic Systems 15 (1), 1729881417748446, 2018 | 3* | 2018 |
| Cross-Modal Learning for Anomaly Detection in Fused Magnesium Smelting Process: Methodology and Benchmark G Wu, Y Zhang, L Deng, J Zhang, T Chai arXiv preprint arXiv:2406.09016, 2024 | 2 | 2024 |
Yebin LiuProfessor, Tsinghua UniversityVerified email at tsinghua.edu.cn
