A Large-Scale Referring Remote Sensing Image Segmentation Dataset and Benchmark

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R. Li, K. Li, Y.-C. Kuo, M. Shu, X. Qi, X. Shen, and J. Jia, “Referring image segmentation via recurrent refinement networks,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 2018, pp. 5745–5753

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L. Ye, M. Rochan, Z. Liu, and Y. Wang, “Cross-modal self-attention network for referring image segmentation,” in Proceedings of the IEEE/CVF conference on computer vision and pattern recognition , 2019, pp. 10 502–10 511

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S. Huang, T. Hui, S. Liu, G. Li, Y. Wei, J. Han, L. Liu, and B. Li, “Referring image segmentation via cross-modal progressive comprehension,” in Proceedings of the IEEE/CVF conference on computer vision and pattern recognition , 2020, pp. 10 488–10 497

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Z. Hu, G. Feng, J. Sun, L. Zhang, and H. Lu, “Bi-directional relationship inferring network for referring image segmentation,” in Proceedings of the IEEE/CVF conference on computer vision and pattern recognition , 2020, pp. 4424–4433

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2021

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S. Liu, T. Hui, S. Huang, Y. Wei, B. Li, and G. Li, “Cross-modal progressive comprehension for referring segmentation,” IEEE Transactions on Pattern Analysis and Machine Intelligence , vol. 44, no. 9, pp. 4761–4775, 2021

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Y. Jing, T. Kong, W. Wang, L. Wang, L. Li, and T. Tan, “Locate then segment: A strong pipeline for referring image segmentation,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , 2021, pp. 9858–9867

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Z. Yang, J. Wang, Y. Tang, K. Chen, H. Zhao, and P. H. Torr, “Lavt: Language-aware vision transformer for referring image segmentation,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , 2022, pp. 18 155–18 165

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C. Liu, H. Ding, and X. Jiang, “Gres: Generalized referring expression segmentation,” in Proceedings of the IEEE/CVF conference on computer vision and pattern recognition , 2023, pp. 23 592–23 601

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H. Ding, C. Liu, S. He, X. Jiang, and C. C. Loy, “Mevis: A large-scale benchmark for video segmentation with motion expressions,” in Proceedings of the IEEE/CVF international conference on computer vision , 2023, pp. 2694–2703

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X. Wang, S. Li, K. Kallidromitis, Y. Kato, K. Kozuka, and T. Darrell, “Hierarchical open-vocabulary universal image segmentation,” Advances in Neural Information Processing Systems , vol. 36, 2024

2024

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S. Lei, X. Xiao, T. Zhang, H.-C. Li, Z. Shi, and Q. Zhu, “Exploring fine-grained image-text alignment for referring remote sensing image segmentation,” IEEE Transactions on Geoscience and Remote Sensing , 2024

2024

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S. Ha, C. Kim, D. Kim, J. Lee, S. Lee, and J. Lee, “Finding nemo: Negative-mined mosaic augmentation for referring image segmentation,” in European Conference on Computer Vision . Springer, 2024, pp. 121–137

2024

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Y. Yang, C. Ma, J. Yao, Z. Zhong, Y. Zhang, and Y. Wang, “Remamber: Referring image segmentation with mamba twister,” in European Conference on Computer Vision . Springer, 2024, pp. 108–126

2024

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