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Referring Remote Sensing Image Segmentation provides a flexible and fine-grained framework for remote sensing scene analysis via vision-language collaborative interpretation.
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2016
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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
2018
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L. Yu, Z. Lin, X. Shen, J. Yang, X. Lu, M. Bansal, and T. L. Berg, “Mattnet: Modular attention network for referring expression comprehension,” in
2018
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S. M. Azimi, C. Henry, L. Sommer, A. Schumann, and E. Vig, “Skyscapes fine-grained semantic understanding of aerial scenes,” in
2019
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L. Ye, M. Rochan, Z. Liu, and Y. Wang, “Cross-modal self-attention network for referring image segmentation,” in
2019
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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
2020
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T. Hui, S. Liu, S. Huang, G. Li, S. Yu, F. Zhang, and J. Han, “Linguistic structure guided context modeling for referring image segmentation,” in
2020
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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
2020
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K. Chen, Z. Zou, and Z. Shi, “Building extraction from remote sensing images with sparse token transformers,”
2021
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A. Radford, J. W. Kim, C. Hallacy, A. Ramesh, G. Goh, S. Agarwal, G. Sastry, A. Askell, P. Mishkin, J. Clark
2021
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W. Li, K. Chen, H. Chen, and Z. Shi, “Geographical knowledge-driven representation learning for remote sensing images,”
2021
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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,”
2021
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Z. Liu, K. Hao, X. Geng, Z. Zou, and Z. Shi, “Dual-branched spatio-temporal fusion network for multihorizon tropical cyclone track forecast,”
2022
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K. Chen, W. Li, J. Chen, Z. Zou, and Z. Shi, “Resolution-agnostic remote sensing scene classification with implicit neural representations,”
2022
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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
2022
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W. Li, K. Chen, and Z. Shi, “Geographical supervision correction for remote sensing representation learning,”
2022
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R. Rombach, A. Blattmann, D. Lorenz, P. Esser, and B. Ommer, “High-resolution image synthesis with latent diffusion models,” in
2022
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X. Sun, P. Wang, W. Lu, Z. Zhu, X. Lu, Q. He, J. Li, X. Rong, Z. Yang, H. Chang
2022
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2022
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J. Li, D. Li, C. Xiong, and S. Hoi, “Blip: Bootstrapping language-image pre-training for unified vision-language understanding and generation,” in
2022
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K. Zhou, J. Yang, C. C. Loy, and Z. Liu, “Learning to prompt for vision-language models,”
2022
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K. Zhou, J. Yang, C. C. Loy, and Z. Liu, “Conditional prompt learning for vision-language models,” in
2022
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M. Jia, L. Tang, B.-C. Chen, C. Cardie, S. Belongie, B. Hariharan, and S.-N. Lim, “Visual prompt tuning,” in
2022
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Y. Zhong, J. Yang, P. Zhang, C. Li, N. Codella, L. H. Li, L. Zhou, X. Dai, L. Yuan, Y. Li
2022
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E. J. Hu, Y. Shen, P. Wallis, Z. Allen-Zhu, Y. Li, S. Wang, L. Wang, W. Chen
2022
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Z. Wang, Y. Lu, Q. Li, X. Tao, Y. Guo, M. Gong, and T. Liu, “Cris: Clip-driven referring image segmentation,” in
2022
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K. Chen, X. Jiang, Y. Hu, X. Tang, Y. Gao, J. Chen, and W. Xie, “Ovarnet: Towards open-vocabulary object attribute recognition,” in
2023
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2023
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A. Kirillov, E. Mintun, N. Ravi, H. Mao, C. Rolland, L. Gustafson, T. Xiao, S. Whitehead, A. C. Berg, W.-Y. Lo
2023
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K. Chen, W. Li, S. Lei, J. Chen, X. Jiang, Z. Zou, and Z. Shi, “Continuous remote sensing image super-resolution based on context interaction in implicit function space,”
2023
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J. Bai, S. Bai, Y. Chu, Z. Cui, K. Dang, X. Deng, Y. Fan, W. Ge, Y. Han, F. Huang
2023
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M. U. Khattak, H. Rasheed, M. Maaz, S. Khan, and F. S. Khan, “Maple: Multi-modal prompt learning,” in
2023
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X. Li, C. Wen, Y. Hu, and N. Zhou, “Rs-clip: Zero shot remote sensing scene classification via contrastive vision-language supervision,”
2023
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2024
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S.-A. Liu, Y. Zhang, Z. Qiu, H. Xie, Y. Zhang, and T. Yao, “Caris: Context-aware referring image segmentation,” in
2023
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Y. Hu, Q. Wang, W. Shao, E. Xie, Z. Li, J. Han, and P. Luo, “Beyond one-to-one: Rethinking the referring image segmentation,” in
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Y. Cho, H. Yu, and S.-J. Kang, “Cross-aware early fusion with stage-divided vision and language transformer encoders for referring image segmentation,”
2023
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Z. Xu, Z. Chen, Y. Zhang, Y. Song, X. Wan, and G. Li, “Bridging vision and language encoders: Parameter-efficient tuning for referring image segmentation,” in
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Z. Yuan, L. Mou, Y. Hua, and X. X. Zhu, “Rrsis: Referring remote sensing image segmentation,”
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Q. Ma, L. Li, X. Lu, L. Jiao, F. Liu, W. Ma, X. Liu, and L. Sun, “Lscf: Long-term semantic-guidance convformer for referring remote sensing image segmentation,”
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Y. Li, W. Jin, S. Qiu, and Q. Sun, “Multimodal prompt-guided bidirectional fusion for referring remote sensing image segmentation,”
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Y. Pan, R. Sun, Y. Wang, T. Zhang, and Y. Zhang, “Rethinking the implicit optimization paradigm with dual alignments for referring remote sensing image segmentation,” in
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