| Learning for Disparity Estimation through Feature Constancy Z Liang, Y Feng, G Yulan, L Hengzhu, W Chen, Q Linbo, Z Li, Z Jianfeng Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018 | 389* | 2018 |
| Learning parallax attention for stereo image super-resolution L Wang, Y Wang, Z Liang, Z Lin, J Yang, W An, Y Guo Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2019 | 273 | 2019 |
| Multi-Level Context Ultra-Aggregation for Stereo Matching GY Nie, MM Cheng, Y Liu, Z Liang, DP Fan, Y Liu, Y Wang Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2019 | 116 | 2019 |
| Stereo Matching Using Multi-level Cost Volume and Multi-scale Feature Constancy Z Liang, Y Guo, Y Feng, W Chen, L Qiao, L Zhou, J Zhang, H Liu IEEE transactions on pattern analysis and machine intelligence, 2019 | 113 | 2019 |
| Parallax attention for unsupervised stereo correspondence learning L Wang, Y Guo, Y Wang, Z Liang, Z Lin, J Yang, W An IEEE transactions on pattern analysis and machine intelligence, 2020 | 101 | 2020 |
| Ranking Support Vector Machine with Kernel Approximation K Chen, R Li, Y Dou, Z Liang, Q Lv Computational intelligence and neuroscience 2017, 2017 | 28 | 2017 |
| Efficient deep learning for stereo matching with larger image patches Y Feng, Z Liang, H Liu 2017 10th International Congress on Image and Signal Processing, BioMedical …, 2017 | 17 | 2017 |
| Real-time hardware accelerator for single image haze removal using dark channel prior and guided filter Z Liang, H Liu, B Zhang, B Wang IEICE Electronics Express 11 (24), 20141002-20141002, 2014 | 17 | 2014 |
| Multi-dimensional cooperative network for stereo matching W Chen, X Jia, M Wu, Z Liang IEEE Robotics and Automation Letters 7 (1), 581-587, 2021 | 14 | 2021 |
| Mirror image: newfangled cell-level layout technique for single-event transient mitigation P Huang, S Chen, Z Liang, J Chen, C Hu, Y He Chinese science bulletin 59 (23), 2850-2858, 2014 | 14 | 2014 |
| Adversarial style discrepancy minimization for unsupervised domain adaptation X Luo, W Chen, Z Liang, C Li, Y Tan Neural Networks 157, 216-225, 2023 | 10 | 2023 |
| Bidirectional Stereo Matching Network With Double Cost Volumes X Jia, W Chen, Z Liang IEEE Access 9, 19651-19658, 2021 | 9 | 2021 |
| A refinement framework for background subtraction based on color and depth data Z Liang, X Liu, H Liu, W Chen 2016 IEEE international conference on image processing (ICIP), 271-275, 2016 | 9 | 2016 |
| Multi-scale cost volumes cascade network for stereo matching X Jia, W Chen, C Li, Z Liang, M Wu, Y Tan, L Huang 2021 IEEE International Conference on Robotics and Automation (ICRA), 8657-8663, 2021 | 8 | 2021 |
| A joint 2D-3D complementary network for stereo matching X Jia, W Chen, Z Liang, X Luo, M Wu, C Li, Y He, Y Tan, L Huang Sensors 21 (4), 1430, 2021 | 6 | 2021 |
| Improving stereo matching by incorporating geometry prior into ConvNet Z Liang, H Liu, L Qiao, Y Feng, W Chen Electronics Letters 53 (17), 1194-1196, 2017 | 6 | 2017 |
| Fast and Accurate Lane Detection via Frequency Domain Learning Y He, W Chen, Z Liang, D Chen, Y Tan, X Luo, C Li, Y Guo Proceedings of the 29th ACM International Conference on Multimedia, 890-898, 2021 | 5 | 2021 |
| A Unified Framework for Depth Prediction from a Single Image and Binocular Stereo Matching W Chen, X Luo, Z Liang, C Li, M Wu, Y Gao, X Jia Remote Sensing 12 (3), 588, 2020 | 4 | 2020 |
| Pseudo-label Correction and Learning For Semi-Supervised Object Detection Y He, W Chen, K Liang, Y Tan, Z Liang, Y Guo arXiv preprint arXiv:2303.02998, 2023 | 1 | 2023 |
| Instance-specific algorithm selection via multi-output learning K Chen, Y Dou, Q Lv, Z Liang Tsinghua Science and Technology 22 (2), 210-217, 2017 | 1 | 2017 |
