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In computer vision, Image Difference Captioning (IDC) is crucial for accurately describing variations between closely related images.
Papineni, K., Roukos, S., Ward, T., Zhu, W.J.: Bleu: a method for automatic evaluation of machine translation. In: Proceedings of the 40th annual meeting of the Association for Computational Linguistics. pp. 311–318 (2002)
2002
Earlier work this paper cites.
Lin, C.Y.: Rouge: A package for automatic evaluation of summaries. In: Text summarization branches out. pp. 74–81 (2004)
2004
Earlier work this paper cites.
Banerjee, S., Lavie, A.: 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. pp. 65–72 (2005)
2005
Earlier work this paper cites.
Lin, T.Y., Maire, M., Belongie, S., Hays, J., Perona, P., Ramanan, D., Dollár, P., Zitnick, C.L.: Microsoft coco: Common objects in context. In: Computer Vision–ECCV 2014: 13th European Conference, Zurich, Switzerland, September 6-12, 2014, Proceedings, Part V 13. pp. 740–755. Springer (2014)
2014
Earlier work this paper cites.
2014
Earlier work this paper cites.
Antol, S., Agrawal, A., Lu, J., Mitchell, M., Batra, D., Zitnick, C.L., Parikh, D.: Vqa: Visual question answering. In: Proceedings of the IEEE international conference on computer vision. pp. 2425–2433 (2015)
2015
Earlier work this paper cites.
Plummer, B.A., Wang, L., Cervantes, C.M., Caicedo, J.C., Hockenmaier, J., Lazebnik, S.: Flickr30k entities: Collecting region-to-phrase correspondences for richer image-to-sentence models. In: Proceedings of the IEEE international conference on computer vision. pp. 2641–2649 (2015)
2015
Earlier work this paper cites.
Vedantam, R., Lawrence Zitnick, C., Parikh, D.: Cider: Consensus-based image description evaluation. In: Proceedings of the IEEE conference on computer vision and pattern recognition. pp. 4566–4575 (2015)
2015
Earlier work this paper cites.
Johnson, J., Hariharan, B., Van Der Maaten, L., Fei-Fei, L., Lawrence Zitnick, C., Girshick, R.: Clevr: A diagnostic dataset for compositional language and elementary visual reasoning. In: Proceedings of the IEEE conference on computer vision and pattern recognition. pp. 2901–2910 (2017)
2017
Earlier work this paper cites.
2018
Earlier work this paper cites.
2018
Earlier work this paper cites.
2018
Earlier work this paper cites.
2019
Earlier work this paper cites.
Hudson, D.A., Manning, C.D.: Gqa: A new dataset for real-world visual reasoning and compositional question answering. In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition. pp. 6700–6709 (2019)
2019
Cited alongside, same era.
Park, D.H., Darrell, T., Rohrbach, A.: Robust change captioning. In: Proceedings of the IEEE/CVF International Conference on Computer Vision. pp. 4624–4633 (2019)
2019
Cited alongside, same era.
2019
Cited alongside, same era.
Brown, T.B.: Language models are few-shot learners. arXiv preprint arXiv:2005.14165 (2020)
2020
Cited alongside, same era.
Brooks, T., Holynski, A., Efros, A.A.: Instructpix2pix: Learning to follow image editing instructions. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 18392–18402 (2023)
2023
Later among the works it cites.
Chiang, W.L., Li, Z., Lin, Z., Sheng, Y., Wu, Z., Zhang, H., Zheng, L., Zhuang, S., Zhuang, Y., Gonzalez, J.E., Stoica, I., Xing, E.P.: Vicuna: An open-source chatbot impressing gpt-4 with 90%* chatgpt quality (March 2023), https://lmsys.org/blog/2023-03-30-vicuna/
2023
Later among the works it cites.
Li, J., Li, D., Savarese, S., Hoi, S.: Blip-2: Bootstrapping language-image pre-training with frozen image encoders and large language models. In: International conference on machine learning. pp. 19730–19742. PMLR (2023)
2023
Later among the works it cites.
Liu, H., Li, C., Wu, Q., Lee, Y.J.: Visual instruction tuning (2023)
2023
Later among the works it cites.
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Shi, X., Yang, X., Gu, J., Joty, S., Cai, J.: Finding it at another side: A viewpoint-adapted matching encoder for change captioning. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XIV 16. pp. 574–590. Springer (2020)
2020
Cited alongside, same era.
Kim, H., Kim, J., Lee, H., Park, H., Kim, G.: Agnostic change captioning with cycle consistency. In: Proceedings of the IEEE/CVF International Conference on Computer Vision. pp. 2095–2104 (2021)
2021
Cited alongside, same era.
Radford, A., Kim, J.W., Hallacy, C., Ramesh, A., Goh, G., Agarwal, S., Sastry, G., Askell, A., Mishkin, P., Clark, J., et al.: Learning transferable visual models from natural language supervision. In: ICML (2021)
2021
Cited alongside, same era.
2021
Cited alongside, same era.
Alayrac, J.B., Donahue, J., Luc, P., Miech, A., Barr, I., Hasson, Y., Lenc, K., Mensch, A., Millican, K., Reynolds, M., et al.: Flamingo: a visual language model for few-shot learning. Advances in neural information processing systems 35
2022
Cited alongside, same era.
2022
Cited alongside, same era.
Sun, Y., Li, L., Yao, T., Lu, T., Zheng, B., Yan, C., Zhang, H., Bao, Y., Ding, G., Slabaugh, G.: Bidirectional difference locating and semantic consistency reasoning for change captioning. International Journal of Intelligent Systems 37
2022
Cited alongside, same era.
Yao, L., Wang, W., Jin, Q.: Image difference captioning with pre-training and contrastive learning. In: Proceedings of the AAAI Conference on Artificial Intelligence. vol. 36, pp. 3108–3116 (2022)
2022
Cited alongside, same era.
Tang, Y., Wang, W., Zhang, C., Liu, J., Zhao, Y.: Temporal action proposal generation with action frequency adaptive network. IEEE Transactions on Multimedia 26
2023
Later among the works it cites.
2023
Later among the works it cites.
Tu, Y., Li, L., Su, L., Du, J., Lu, K., Huang, Q.: Adaptive representation disentanglement network for change captioning. IEEE Transactions on Image Processing (2023)
2023
Later among the works it cites.
Tu, Y., Li, L., Su, L., Lu, K., Huang, Q.: Neighborhood contrastive transformer for change captioning. IEEE Transactions on Multimedia (2023)
2023
Later among the works it cites.
Tu, Y., Li, L., Su, L., Zha, Z.J., Yan, C., Huang, Q.: Self-supervised cross-view representation reconstruction for change captioning. In: Proceedings of the IEEE/CVF International Conference on Computer Vision. pp. 2805–2815 (2023)
2023
Later among the works it cites.
2023
Later among the works it cites.
2023
Later among the works it cites.
Tang, Y., Wang, W., Zhang, C., Liu, J., Zhao, Y.: Learnable feature augmentation framework for temporal action localization. IEEE Transactions on Image Processing 33
2024
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