[66] J. Wang, K. Sun, T. Cheng, B. Jiang, C. Deng, Y. Zhao, D. Liu, Y. Mu, M. Tan, X. Wang, et al. Deep high-resolution representation learning for visual recognition. IEEE transactions on pattern analysis and machine intelligence, 43(10):3349-3364, 2020.
[67] W. Wang, J. Dai, Z. Chen, Z. Huang, Z. Li, X. Zhu, X. Hu, T. Lu, L. Lu, H. Li, et al. Internimage: Exploring large-scale vision foundation models with deformable convolutions. arXiv preprint arXiv:2211.05778, 2022.
[68] W. Wang, T. Zhou, F. Yu, J. Dai, E. Konukoglu, and L. Van Gool. Exploring cross-image pixel contrast for semantic segmentation. In Proceedings of the IEEE/CVF International Conference on Computer Vision, pages 7303-7313, 2021.
[69] X. Wang, R. Girshick, A. Gupta, and K. He. Non-local neural networks. In Proceedings of the IEEE conference on computer vision and pattern recognition, pages 7794-7803, 2018.
[70] T. Xiao, Y. Liu, B. Zhou, Y. Jiang, and J. Sun. Unified perceptual parsing for scene understanding. In Proceedings of the European conference on computer vision (ECCV), pages 418-434, 2018.
[71] E. Xie, W. Wang, Z. Yu, A. Anandkumar, J. M. Alvarez, and P. Luo. Segformer: Simple and efficient design for semantic segmentation with transformers. Advances in Neural Information Processing Systems, 34:12077-12090, 2021.
[72] S. Xie, R. Girshick, P. Dollar, Z. Tu, and K. He. Aggregated residual transformations for deep neural networks. In Proceedings of the IEEE conference on computer vision and pattern recognition, pages 1492-1500, 2017.
[73] H. Xu, C. Jiang, X. Liang, and Z. Li. Spatial-aware graph relation network for large-scale object detection. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pages 9298-9307, 2019.
[74] M. Yang, K. Yu, C. Zhang, Z. Li, and K. Yang. Denseaspp for semantic segmentation in street scenes. In Proceedings of the IEEE conference on computer vision and pattern recognition, pages 3684-3692, 2018.
[75] M. Yin, Z. Yao, Y. Cao, X. Li, Z. Zhang, S. Lin, and H. Hu. Disentangled non-local neural networks. In Computer Vision-ECCV 2020: 16th European Conference, Glasgow, UK, August 23-28, 2020, Proceedings, Part XV 16, pages 191-207. Springer, 2020.
[76] C. Yu, J. Wang, C. Gao, G. Yu, C. Shen, and N. Sang. Context prior for scene segmentation. In Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, pages 12416-12425, 2020.
[77] F. Yu and V. Koltun. Multi-scale context aggregation by dilated convolutions. arXiv preprint arXiv:1511.07122, 2015.
[78] W. Yu, M. Luo, P. Zhou, C. Si, Y. Zhou, X. Wang, J. Feng, and S. Yan. Metaformer is actually what you need for vision. In Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, pages 10819-10829, 2022.
[79] Y. Yuan, X. Chen, and J. Wang. Object-contextual representations for semantic segmentation. In Computer Vision-ECCV 2020: 16th European Conference, Glasgow, UK, August 23-28, 2020, Proceedings, Part VI 16, pages 173-190. Springer, 2020.
[80] Y. Yuan, L. Huang, J. Guo, C. Zhang, X. Chen, and J. Wang. Ocnet: Object context for semantic segmentation. International Journal of Computer Vision, 129(8):2375-2398, 2021.
[81] Y. Yuan, J. Xie, X. Chen, and J. Wang. Segfix: Model-agnostic boundary refinement for segmentation. In Computer Vision-ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XII 16, pages 489–506. Springer, 2020.
[82] W. Zhang, J. Pang, K. Chen, and C. C. Loy. K-net: Towards unified image segmentation. Advances in Neural Information Processing Systems, 34:10326-10338, 2021.
[83] H. Zhao, J. Shi, X. Qi, X. Wang, and J. Jia. Pyramid scene parsing network. In Proceedings of the IEEE conference on computer vision and pattern recognition, pages 2881-2890, 2017.
[84] S. Zhao, Y. Wang, Z. Yang, and D. Cai. Region mutual information loss for semantic segmentation. Advances in Neural Information Processing Systems, 32, 2019.
[85] X. Zhao, R. Vemulapalli, P. A. Mansfield, B. Gong, B. Green, L. Shapira, and Y. Wu. Contrastive learning for label efficient semantic segmentation. In Proceedings of the IEEE/CVF International Conference on Computer Vision, pages 10623-10633, 2021.