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Composed image retrieval attempts to retrieve an image of interest from gallery images through a composed query of a reference image and its corresponding modified text.
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Gordo, A., Almazán, J., Revaud, J., Larlus, D.: Deep image retrieval: Learning global representations for image search. In: Computer Vision–ECCV 2016: 14th European Conference, Amsterdam, The Netherlands, October 11-14, 2016, Proceedings, Part VI 14. pp. 241–257. Springer (2016)
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Mai, L., Jin, H., Lin, Z., Fang, C., Brandt, J., Liu, F.: Spatial-semantic image search by visual feature synthesis. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. pp. 4718–4727 (2017)
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Vo, N., Jiang, L., Sun, C., Murphy, K., Li, L.J., Fei-Fei, L., Hays, J.: Composing text and image for image retrieval-an empirical odyssey. In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition. pp. 6439–6448 (2019)
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Brown, T., Mann, B., Ryder, N., Subbiah, M., Kaplan, J.D., Dhariwal, P., Neelakantan, A., Shyam, P., Sastry, G., Askell, A., et al.: Language models are few-shot learners. Advances in neural information processing systems 33
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Chen, Y., Gong, S., Bazzani, L.: Image search with text feedback by visiolinguistic attention learning. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 3001–3011 (2020)
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Gabbay, A., Cohen, N., Hoshen, Y.: An image is worth more than a thousand words: Towards disentanglement in the wild. Advances in Neural Information Processing Systems 34
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Liu, Z., Rodriguez-Opazo, C., Teney, D., Gould, S.: Image retrieval on real-life images with pre-trained vision-and-language models. In: Proceedings of the IEEE/CVF International Conference on Computer Vision. pp. 2125–2134 (2021)
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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: International conference on machine learning. pp. 8748–8763. PMLR (2021)
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Wu, H., Gao, Y., Guo, X., Al-Halah, Z., Rennie, S., Grauman, K., Feris, R.: The fashion iq dataset: Retrieving images by combining side information and relative natural language feedback. CVPR (2021)
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Baldrati, A., Bertini, M., Uricchio, T., Del Bimbo, A.: Effective conditioned and composed image retrieval combining clip-based features. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 21466–21474 (2022)
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Cohen, N., Gal, R., Meirom, E.A., Chechik, G., Atzmon, Y.: “this is my unicorn, fluffy”: Personalizing frozen vision-language representations. In: European Conference on Computer Vision. pp. 558–577. Springer (2022)
Zhou, K., Yang, J., Loy, C.C., Liu, Z.: Learning to prompt for vision-language models. International Journal of Computer Vision 130
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Li, J., Li, D., Xiong, C., Hoi, S.: Blip: Bootstrapping language-image pre-training for unified vision-language understanding and generation. In: International Conference on Machine Learning. pp. 12888–12900. PMLR (2022)
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Wei, J., Wang, X., Schuurmans, D., Bosma, M., Xia, F., Chi, E., Le, Q.V., Zhou, D., et al.: Chain-of-thought prompting elicits reasoning in large language models. Advances in Neural Information Processing Systems 35
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Zhou, K., Yang, J., Loy, C.C., Liu, Z.: Conditional prompt learning for vision-language models. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 16816–16825 (2022)
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Li, D., Li, J., Le, H., Wang, G., Savarese, S., Hoi, S.C.: LAVIS: A one-stop library for language-vision intelligence. In: Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 3: System Demonstrations). pp. 31–41. Association for Computational Linguistics, Toronto, Canada (Jul 2023), https://aclanthology.org/2023.acl-demo.3
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Liu, P., Yuan, W., Fu, J., Jiang, Z., Hayashi, H., Neubig, G.: Pre-train, prompt, and predict: A systematic survey of prompting methods in natural language processing. ACM Computing Surveys 55
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Saito, K., Sohn, K., Zhang, X., Li, C.L., Lee, C.Y., Saenko, K., Pfister, T.: Pic2word: Mapping pictures to words for zero-shot composed image retrieval. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 19305–19314 (2023)
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Yang, Y., Panagopoulou, A., Zhou, S., Jin, D., Callison-Burch, C., Yatskar, M.: Language in a bottle: Language model guided concept bottlenecks for interpretable image classification. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 19187–19197 (2023)
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