Mobilenetv2: Inverted residuals and linear bottlenecks M Sandler, A Howard, M Zhu, A Zhmoginov, LC Chen Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018 | 22658 | 2018 |
Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected crfs LC Chen, G Papandreou, I Kokkinos, K Murphy, AL Yuille IEEE transactions on pattern analysis and machine intelligence 40 (4), 834-848, 2018 | 20286 | 2018 |
Encoder-decoder with atrous separable convolution for semantic image segmentation LC Chen, Y Zhu, G Papandreou, F Schroff, H Adam Proceedings of the European conference on computer vision (ECCV), 801-818, 2018 | 15321 | 2018 |
Rethinking atrous convolution for semantic image segmentation LC Chen, G Papandreou, F Schroff, H Adam arXiv preprint arXiv:1706.05587, 2017 | 10356 | 2017 |
Searching for mobilenetv3 A Howard, M Sandler, G Chu, LC Chen, B Chen, M Tan, W Wang, Y Zhu, ... Proceedings of the IEEE/CVF international conference on computer vision …, 2019 | 7684 | 2019 |
Semantic image segmentation with deep convolutional nets and fully connected crfs LC Chen, G Papandreou, I Kokkinos, K Murphy, AL Yuille arXiv preprint arXiv:1412.7062, 2014 | 5999 | 2014 |
Attention to scale: Scale-aware semantic image segmentation LC Chen, Y Yang, J Wang, W Xu, AL Yuille Proceedings of the IEEE conference on computer vision and pattern …, 2016 | 1627 | 2016 |
Weakly-and semi-supervised learning of a deep convolutional network for semantic image segmentation G Papandreou, LC Chen, KP Murphy, AL Yuille Proceedings of the IEEE international conference on computer vision, 1742-1750, 2015 | 1534 | 2015 |
Inverted residuals and linear bottlenecks: Mobile networks for classification, detection and segmentation A Howard, A Zhmoginov, LC Chen, M Sandler, M Zhu Proc. CVPR, 4510-4520, 2018 | 1224* | 2018 |
Auto-deeplab: Hierarchical neural architecture search for semantic image segmentation C Liu, LC Chen, F Schroff, H Adam, W Hua, AL Yuille, L Fei-Fei Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 1169 | 2019 |
Detectors: Detecting objects with recursive feature pyramid and switchable atrous convolution S Qiao, LC Chen, A Yuille Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021 | 835 | 2021 |
Axial-deeplab: Stand-alone axial-attention for panoptic segmentation H Wang, Y Zhu, B Green, H Adam, A Yuille, LC Chen European conference on computer vision, 108-126, 2020 | 750 | 2020 |
Personlab: Person pose estimation and instance segmentation with a bottom-up, part-based, geometric embedding model G Papandreou, T Zhu, LC Chen, S Gidaris, J Tompson, K Murphy Proceedings of the European conference on computer vision (ECCV), 269-286, 2018 | 722 | 2018 |
Panoptic-DeepLab: A Simple, Strong, and Fast Baseline for Bottom-Up Panoptic Segmentation B Cheng, MD Collins, Y Zhu, T Liu, TS Huang, H Adam, LC Chen arXiv preprint arXiv:1911.10194, 2019 | 647 | 2019 |
Max-deeplab: End-to-end panoptic segmentation with mask transformers H Wang, Y Zhu, H Adam, A Yuille, LC Chen Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021 | 538 | 2021 |
Searching for efficient multi-scale architectures for dense image prediction LC Chen, M Collins, Y Zhu, G Papandreou, B Zoph, F Schroff, H Adam, ... Advances in neural information processing systems 31, 2018 | 479 | 2018 |
Feelvos: Fast end-to-end embedding learning for video object segmentation P Voigtlaender, Y Chai, F Schroff, H Adam, B Leibe, LC Chen Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 474 | 2019 |
Masklab: Instance segmentation by refining object detection with semantic and direction features LC Chen, A Hermans, G Papandreou, F Schroff, P Wang, H Adam Proceedings of the IEEE conference on computer vision and pattern …, 2018 | 462 | 2018 |
Semantic image segmentation with task-specific edge detection using cnns and a discriminatively trained domain transform LC Chen, JT Barron, G Papandreou, K Murphy, AL Yuille Proceedings of the IEEE conference on computer vision and pattern …, 2016 | 425 | 2016 |
Abc-cnn: An attention based convolutional neural network for visual question answering K Chen, J Wang, LC Chen, H Gao, W Xu, R Nevatia arXiv preprint arXiv:1511.05960, 2015 | 390 | 2015 |