Change Captioning in Remote Sensing: Evolution to SAT-Cap -- A Single-Stage Transformer Approach

Y. Qiu, S. Yamamoto, K. Nakashima, R. Suzuki, K. Iwata, H. Kataoka, and Y. Satoh, “Describing and localizing multiple changes with transformers,” in Proceedings of the IEEE/CVF International Conference on Computer Vision , 2021, pp. 1971–1980

1980

Earlier work this paper cites.

K. Papineni, S. Roukos, T. Ward, and W.-J. Zhu, “Bleu: a method for automatic evaluation of machine translation,” in Proceedings of the 40th annual meeting of the Association for Computational Linguistics , 2002, pp. 311–318

2002

Earlier work this paper cites.

C.-Y. Lin, “Rouge: A package for automatic evaluation of summaries,” in Text summarization branches out , 2004, pp. 74–81

2004

Earlier work this paper cites.

S. Banerjee and A. Lavie, “Meteor: An automatic metric for mt evaluation with improved correlation with human judgments,” in Proceedings of the acl workshop on intrinsic and extrinsic evaluation measures for machine translation and/or summarization , 2005, pp. 65–72

2005

Earlier work this paper cites.

C. Song, B. Huang, L. Ke, and K. S. Richards, “Remote sensing of alpine lake water environment changes on the tibetan plateau and surroundings: A review,” ISPRS Journal of Photogrammetry and Remote Sensing , vol. 92, pp. 26–37, 2014

2014

Earlier work this paper cites.

E. A. Wentz, S. Anderson, M. Fragkias, M. Netzband, V. Mesev, S. W. Myint, D. Quattrochi, A. Rahman, and K. C. Seto, “Supporting global environmental change research: A review of trends and knowledge gaps in urban remote sensing,” Remote Sensing , vol. 6, no. 5, pp. 3879–3905, 2014

2014

Earlier work this paper cites.

D. P. Kingma, “Adam: A method for stochastic optimization,” arXiv preprint arXiv:1412.6980 , 2014

Original

2014

Earlier work this paper cites.

O. Vinyals, A. Toshev, S. Bengio, and D. Erhan, “Show and tell: A neural image caption generator,” in Proceedings of the IEEE conference on computer vision and pattern recognition , 2015, pp. 3156–3164

2015

Earlier work this paper cites.

E. Mansimov, E. Parisotto, J. L. Ba, and R. Salakhutdinov, “Generating images from captions with attention,” arXiv preprint arXiv:1511.02793 , 2015

Original

2015

Earlier work this paper cites.

S. Antol, A. Agrawal, J. Lu, M. Mitchell, D. Batra, C. L. Zitnick, and D. Parikh, “Vqa: Visual question answering,” in Proceedings of the IEEE international conference on computer vision , 2015, pp. 2425–2433

2015

Earlier work this paper cites.

F. Yan and K. Mikolajczyk, “Deep correlation for matching images and text,” in Proceedings of the IEEE conference on computer vision and pattern recognition , 2015, pp. 3441–3450

2015

Earlier work this paper cites.

R. Vedantam, C. Lawrence Zitnick, and D. Parikh, “Cider: Consensus-based image description evaluation,” in Proceedings of the IEEE conference on computer vision and pattern recognition , 2015, pp. 4566–4575

2015

Earlier work this paper cites.

S. Reed, Z. Akata, X. Yan, L. Logeswaran, B. Schiele, and H. Lee, “Generative adversarial text to image synthesis,” in International conference on machine learning . PMLR, 2016, pp. 1060–1069

2016

Earlier work this paper cites.

K. He, X. Zhang, S. Ren, and J. Sun, “Deep residual learning for image recognition,” in Proceedings of the IEEE conference on computer vision and pattern recognition , 2016, pp. 770–778

2016

Earlier work this paper cites.

L. Chen, H. Zhang, J. Xiao, L. Nie, J. Shao, W. Liu, and T.-S. Chua, “Sca-cnn: Spatial and channel-wise attention in convolutional networks for image captioning,” in Proceedings of the IEEE conference on computer vision and pattern recognition , 2017, pp. 5659–5667

2017

Earlier work this paper cites.

A. Vaswani, N. Shazeer, N. Parmar, J. Uszkoreit, L. Jones, A. N. Gomez, Ł. Kaiser, and I. Polosukhin, “Attention is all you need,” Advances in neural information processing systems , vol. 30, 2017

2017

Earlier work this paper cites.

J. Hu, L. Shen, and G. Sun, “Squeeze-and-excitation networks,” in Proceedings of the IEEE conference on computer vision and pattern recognition , 2018, pp. 7132–7141

2018

Earlier work this paper cites.

J. Devlin, M.-W. Chang, K. Lee, and K. Toutanova, “Bert: Pre-training of deep bidirectional transformers for language understanding,” arXiv preprint arXiv:1810.04805 , 2018

Original

2018

Earlier work this paper cites.

D. H. Park, T. Darrell, and A. Rohrbach, “Robust change captioning,” in Proceedings of the IEEE/CVF International Conference on Computer Vision , 2019, pp. 4624–4633

2019

Earlier work this paper cites.

S. Lobry, D. Marcos, J. Murray, and D. Tuia, “Rsvqa: Visual question answering for remote sensing data,” IEEE Transactions on Geoscience and Remote Sensing , vol. 58, no. 12, pp. 8555–8566, 2020

2020

Earlier work this paper cites.

H. Chen and Z. Shi, “A spatial-temporal attention-based method and a new dataset for remote sensing image change detection,” Remote Sensing , vol. 12, no. 10, p. 1662, 2020

2020

Cited alongside, same era.

R. Zhao, Z. Shi, and Z. Zou, “High-resolution remote sensing image captioning based on structured attention,” IEEE Transactions on Geoscience and Remote Sensing , vol. 60, pp. 1–14, 2021

2021

Cited alongside, same era.

Q. Cheng, Y. Zhou, P. Fu, Y. Xu, and L. Zhang, “A deep semantic alignment network for the cross-modal image-text retrieval in remote sensing,” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing , vol. 14, pp. 4284–4297, 2021

2021

Cited alongside, same era.

M. Hosseinzadeh and Y. Wang, “Image change captioning by learning from an auxiliary task,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , 2021, pp. 2725–2734

2021

Cited alongside, same era.

K. Kuckreja, M. S. Danish, M. Naseer, A. Das, S. Khan, and F. S. Khan, “Geochat: Grounded large vision-language model for remote sensing,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , 2024, pp. 27 831–27 840

2024

Later among the works it cites.

Z. Zhang, T. Zhao, Y. Guo, and J. Yin, “Rs5m and georsclip: A large scale vision-language dataset and a large vision-language model for remote sensing,” IEEE Transactions on Geoscience and Remote Sensing , 2024

2024

Later among the works it cites.

C. Liu, J. Zhang, K. Chen, M. Wang, Z. Zou, and Z. Shi, “Remote sensing temporal vision-language models: A comprehensive survey,” arXiv preprint arXiv:2412.02573 , 2024

Original

2024

Later among the works it cites.

W. Zhang, M. Cai, T. Zhang, Y. Zhuang, and X. Mao, “Earthgpt: A universal multi-modal large language model for multi-sensor image comprehension in remote sensing domain,” IEEE Transactions on Geoscience and Remote Sensing , 2024

2024