| RefineNet: Multi-Path Refinement Networks for High-Resolution Semantic Segmentation G Lin, A Milan, C Shen, I Reid IEEE Conference on Computer Vision and Pattern Recognition, 2017 | 4023 | 2017 |
| Learning depth from single monocular images using deep convolutional neural fields F Liu, C Shen, G Lin, I Reid IEEE transactions on pattern analysis and machine intelligence 38 (10), 2024 …, 2015 | 1514 | 2015 |
| Efficient piecewise training of deep structured models for semantic segmentation G Lin, C Shen, R Ian, A van dan Hengel IEEE Conference on Computer Vision and Pattern Recognition, 2016 | 1209 | 2016 |
| Deep convolutional neural fields for depth estimation from a single image F Liu, C Shen, G Lin Proceedings of the IEEE conference on computer vision and pattern …, 2015 | 1183 | 2015 |
| Deepemd: Few-shot image classification with differentiable earth mover's distance and structured classifiers C Zhang, Y Cai, G Lin, C Shen Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 951 | 2020 |
| Canet: Class-agnostic segmentation networks with iterative refinement and attentive few-shot learning C Zhang, G Lin, F Liu, R Yao, C Shen Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 697 | 2019 |
| 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 | 498 | 2014 |
| Pyramid graph networks with connection attentions for region-based one-shot semantic segmentation C Zhang, G Lin, F Liu, J Guo, Q Wu, R Yao Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 361 | 2019 |
| Few-shot incremental learning with continually evolved classifiers C Zhang, N Song, G Lin, Y Zheng, P Pan, Y Xu Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 359 | 2021 |
| Crnet: Cross-reference networks for few-shot segmentation W Liu, C Zhang, G Lin, F Liu Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 260 | 2020 |
| CRF learning with CNN features for image segmentation F Liu, G Lin, C Shen Pattern Recognition 48 (10), 2983-2992, 2015 | 248 | 2015 |
| Video object segmentation and tracking: A survey R Yao, G Lin, S Xia, J Zhao, Y Zhou ACM Transactions on Intelligent Systems and Technology (TIST) 11 (4), 1-47, 2020 | 241 | 2020 |
| A general two-step approach to learning-based hashing G Lin, C Shen, D Suter, A Van Den Hengel Proceedings of the IEEE international conference on computer vision, 2552-2559, 2013 | 213 | 2013 |
| Multi-path region mining for weakly supervised 3d semantic segmentation on point clouds J Wei, G Lin, KH Yap, TY Hung, L Xie Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 169 | 2020 |
| A dilated inception network for visual saliency prediction S Yang, G Lin, Q Jiang, W Lin IEEE Transactions on Multimedia 22 (8), 2163-2176, 2019 | 164 | 2019 |
| Monet: Deep motion exploitation for video object segmentation H Xiao, J Feng, G Lin, Y Liu, M Zhang Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018 | 163 | 2018 |
| Exploring context with deep structured models for semantic segmentation G Lin, C Shen, A Hengel, I Reid IEEE Transactions on Pattern Analysis and Machine Intelligence, 2017 | 159 | 2017 |
| Learning hash functions using column generation X Li, G Lin, C Shen, A Hengel, A Dick ICML2013, 2013 | 159 | 2013 |
| Progressive modality reinforcement for human multimodal emotion recognition from unaligned multimodal sequences F Lv, X Chen, Y Huang, L Duan, G Lin Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 151 | 2021 |
| Fast training of triplet-based deep binary embedding networks B Zhuang, G Lin, C Shen, I Reid Proceedings of the IEEE conference on computer vision and pattern …, 2016 | 145 | 2016 |
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