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Intell."],"published-print":{"date-parts":[[2025,12]]},"abstract":"<jats:title>Abstract<\/jats:title>\n          <jats:p>In the real world, where information is abundant and diverse across different modalities, understanding and utilizing various data types to improve retrieval systems is a key focus of research. Multimodal composite retrieval integrates diverse modalities such as text, image and audio to provide more accurate, personalized, and contextually relevant results. However, alongside retrieval, multimodal composite editing plays a crucial role in enabling users to refine or modify retrieved content through intuitive interactions, which enhances the overall effectiveness of multimodal systems. The task of multimodal composite editing is becoming increasingly critical due to its applications in various domains, including creative industries, education, and user-driven content modification. A comprehensive evaluation and usage guide is needed to fully assess its capabilities and limitations, since it complements and extends the functionalities provided by multimodal retrieval systems. To facilitate a deeper understanding of this promising direction, this survey explores multimodal composite editing and retrieval in depth, covering image-text composite editing, image-text composite retrieval, and other multimodal composite retrieval. In this survey, we systematically organize the application scenarios, methods, benchmarks, experiments, and future directions. Multimodal learning has gained significant popularity in the era of large AI models, as demonstrated by the growing number of surveys in multimodal learning and vision-language models with Transformers. To the best of our knowledge, this survey is the first comprehensive review of the literature on multimodal composite retrieval, which is a timely complement of multimodal fusion to existing reviews. Moreover, this paper bridges the gap between large model architectures and their applications in both retrieval and editing tasks, highlighting their intertwined roles in advancing multimodal systems.<\/jats:p>","DOI":"10.1007\/s44267-025-00086-x","type":"journal-article","created":{"date-parts":[[2025,7,16]],"date-time":"2025-07-16T03:13:29Z","timestamp":1752635609000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["A survey of multimodal composite editing and retrieval"],"prefix":"10.1007","volume":"3","author":[{"given":"Suyan","family":"Li","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fuxiang","family":"Huang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5305-8543","authenticated-orcid":false,"given":"Lei","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,7,16]]},"reference":[{"issue":"5","key":"86_CR1","doi-asserted-by":"publisher","first-page":"2687","DOI":"10.1109\/TCSVT.2021.3080920","volume":"32","author":"S. 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New York: ACM."},{"key":"86_CR56","doi-asserted-by":"publisher","first-page":"42534","DOI":"10.1109\/ACCESS.2023.3269847","volume":"11","author":"Y. Watanabe","year":"2023","unstructured":"Watanabe, Y., Togo, R., Maeda, K., Ogawa, T., & Haseyama, M. (2023). Text-guided image manipulation via generative adversarial network with referring image segmentation-based guidance. IEEE Access, 11, 42534\u201342545.","journal-title":"IEEE Access"},{"key":"86_CR57","first-page":"25146","volume-title":"Proceedings of the 36th international conference on neural information processing systems","author":"Y. Zhu","year":"2022","unstructured":"Zhu, Y., Liu, H., Song, Y., Yuan, Z., Han, X., Yuan, C., Chen, Q., & Wang, J. (2022). One model to edit them all: free-form text-driven image manipulation with semantic modulations. In S. Koyejo, S. Mohamed, A. Agarwal, D. Belgrave, K. Cho, & A. Oh (Eds.), Proceedings of the 36th international conference on neural information processing systems (pp. 25146\u201325159). Red Hook: Curran Associates."},{"issue":"4","key":"86_CR58","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3450626.3459838","volume":"40","author":"O. Tov","year":"2021","unstructured":"Tov, O., Alaluf, Y., Nitzan, Y., Patashnik, O., & Cohen-Or, D. (2021). Designing an encoder for stylegan image manipulation. ACM Transactions on Graphics, 40(4), 1\u201314.","journal-title":"ACM Transactions on Graphics"},{"key":"86_CR59","first-page":"1","volume-title":"ACM SIGGRAPH 2022 conference","author":"R. Abdal","year":"2022","unstructured":"Abdal, R., Zhu, P., Femiani, J., Mitra, N., & Wonka, P. (2022). Clip2stylegan: unsupervised extraction of stylegan edit directions. In ACM SIGGRAPH 2022 conference (pp. 1\u20139). New York: ACM."},{"key":"86_CR60","first-page":"18072","volume-title":"Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition","author":"T. Wei","year":"2022","unstructured":"Wei, T., Chen, D., Zhou, W., Liao, J., Tan, Z., Yuan, L., Zhang, W., & Yu, N. (2022). Hairclip: design your hair by text and reference image. In Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition (pp. 18072\u201318081). Piscataway: IEEE."},{"key":"86_CR61","unstructured":"Lyu, Y., Zhao, K., Peng, B., Jiang, Y., Zhang, Y., & Dong, J. (2023). Deltaspace: a semantic-aligned feature space for flexible text-guided image editing. arXiv preprint. arXiv:2310.08785."},{"key":"86_CR62","unstructured":"Hou, X., Shen, L., Patashnik, O., Cohen-Or, D., & Huang, H. (2022). Feat: face editing with attention. arXiv preprint. arXiv:2202.02713."},{"key":"86_CR63","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2023.109458","volume":"139","author":"C. Xiao","year":"2023","unstructured":"Xiao, C., Yang, Q., Xu, X., Zhang, J., Zhou, F., & Zhang, C. (2023). Where you edit is what you get: text-guided image editing with region-based attention. Pattern Recognition, 139, 109458.","journal-title":"Pattern Recognition"},{"key":"86_CR64","first-page":"895","volume-title":"Proceedings of the IEEE\/CVF winter conference on applications of computer vision","author":"U. Kocasari","year":"2022","unstructured":"Kocasari, U., Dirik, A., Tiftikci, M., & Yanardag, P. (2022). StyleMC: multi-channel based fast text-guided image generation and manipulation. In Proceedings of the IEEE\/CVF winter conference on applications of computer vision (pp. 895\u2013904). Piscataway: IEEE."},{"key":"86_CR65","unstructured":"Andonian, A., Osmany, S., Cui, A., Park, Y., Jahanian, A., Torralba, A., & Bau, D. (2021). Paint by word. arXiv preprint. arXiv:2103.10951."},{"key":"86_CR66","first-page":"88","volume-title":"Proceedings of the 17th European conference on computer vision","author":"K. Crowson","year":"2022","unstructured":"Crowson, K., Biderman, S., Kornis, D., Stander, D., Hallahan, E., Castricato, L., & Raff, E. (2022). VQGAN-CLIP: open domain image generation and editing with natural language guidance. In S. Avidan, G. J. Brostow, M. Ciss\u00e9, G. M. Farinella, & T. Hassner (Eds.), Proceedings of the 17th European conference on computer vision (pp. 88\u2013105). Cham: Springer."},{"key":"86_CR67","first-page":"2433","volume-title":"Proceedings of the IEEE international conference on image processing","author":"T. Haruyama","year":"2021","unstructured":"Haruyama, T., Togo, R., Maeda, K., Ogawa, T., & Haseyama, M. (2021). Segmentation-aware text-guided image manipulation. In Proceedings of the IEEE international conference on image processing (pp. 2433\u20132437). Piscataway: IEEE."},{"key":"86_CR68","first-page":"7880","volume-title":"Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition","author":"L. Bowen","year":"2020","unstructured":"Bowen, L., Qi, X., Lukasiewicz, T., Philip, H. S., & Manigan, T. (2020). Text-guided image manipulation. In Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition (pp. 7880\u20137889). Piscataway: IEEE."},{"key":"86_CR69","first-page":"2065","volume-title":"Proceedings of the 33rd international conference on neural information processing systems","author":"L. Bowen","year":"2019","unstructured":"Bowen, L., Qi, X., Lukasiewicz, T., & Torr, P. (2019). Controllable text-to-image generation. In H. Wallach, H. Larochelle, A. Beygelzimer, F. d\u2019Alch\u00e9 Buc, E. Fox, & R. Garnett (Eds.), Proceedings of the 33rd international conference on neural information processing systems (pp. 2065\u20132075). Red Hook: Curran Associates."},{"key":"86_CR70","unstructured":"Shinagawa, S., Yoshino, K., Sakti, S., Suzuki, Y., & Nakamura, S. (2018). Interactive image manipulation with natural language instruction commands. arXiv preprint. arXiv:1802.08645."},{"key":"86_CR71","unstructured":"Radford, A., Metz, L., & Chintala, S. (2015). Unsupervised representation learning with deep convolutional generative adversarial networks. arXiv preprint. arXiv:1511.06434."},{"key":"86_CR72","first-page":"8721","volume-title":"Proceedings of the IEEE conference on computer vision and pattern recognition","author":"J. Chen","year":"2018","unstructured":"Chen, J., Shen, Y., Gao, J., Liu, J., & Liu, X. (2018). Language-based image editing with recurrent attentive models. In Proceedings of the IEEE conference on computer vision and pattern recognition (pp. 8721\u20138729). Piscataway: IEEE."},{"key":"86_CR73","first-page":"89","volume-title":"Proceedings of the 16th European conference on computer vision","author":"X. Liu","year":"2020","unstructured":"Liu, X., Lin, Z., Zhang, J., Zhao, H., Tran, Q., Wang, X., & Li, H. (2020). Open-edit: open-domain image manipulation with open-vocabulary instructions. In A. Vedaldi, H. Bischof, T. Brox, & J.-M. Frahm (Eds.), Proceedings of the 16th European conference on computer vision (pp. 89\u2013106). Cham: Springer."},{"key":"86_CR74","first-page":"9971","volume-title":"Proceedings of the 37th AAAI conference on artificial intelligence","author":"M. Tao","year":"2023","unstructured":"Tao, M., Bao, B.-K., Tang, H., Wu, F., Wei, L., & Tian, Q. (2023). De-net: dynamic text-guided image editing adversarial networks. In Proceedings of the 37th AAAI conference on artificial intelligence (pp. 9971\u20139979). Palo Alto: AAAI."},{"key":"86_CR75","unstructured":"Mirza, M., & Osindero, S. (2014). Conditional generative adversarial nets. arXiv preprint. arXiv:1411.1784."},{"key":"86_CR76","first-page":"172","volume-title":"Proceedings of the 15th European conference on computer vision","author":"X. Huang","year":"2018","unstructured":"Huang, X., Liu, M.-Y., Belongie, S., & Kautz, J. (2018). Multimodal unsupervised image-to-image translation. In V. Ferrari, M. Hebert, C. Sminchisescu, & Y. Weiss (Eds.), Proceedings of the 15th European conference on computer vision (pp. 172\u2013189). Cham: Springer."},{"key":"86_CR77","first-page":"1294","volume-title":"Proceedings of the 32nd international conference on neural information processing systems","author":"A. Gonzalez-Garcia","year":"2018","unstructured":"Gonzalez-Garcia, A., van de Weijer, J., & Bengio, Y. (2018). Image-to-image translation for cross-domain disentanglement. In S. Bengio, H. Wallach, H. Larochelle, K. Grauman, N. Cesa-Bianchi, & R. Garnett (Eds.), Proceedings of the 32nd international conference on neural information processing systems (pp. 1294\u20131305). Red Hook: Curran Associates."},{"key":"86_CR78","unstructured":"Liu, Y., De Nadai, M., Yao, J., Sebe, N., Lepri, B., & Alameda-Pineda, X. (2020). Gmm-unit: unsupervised multi-domain and multi-modal image-to-image translation via attribute Gaussian mixture modeling. arXiv preprint. arXiv:2003.06788."},{"key":"86_CR79","first-page":"4401","volume-title":"Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition","author":"T. Karras","year":"2019","unstructured":"Karras, T., Laine, S., & Aila, T. (2019). A style-based generator architecture for generative adversarial networks. In Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition (pp. 4401\u20134410). Piscataway: IEEE."},{"key":"86_CR80","first-page":"8110","volume-title":"Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition","author":"T. Karras","year":"2020","unstructured":"Karras, T., Laine, S., Aittala, M., Hellsten, J., Lehtinen, J., & Aila, T. (2020). Analyzing and improving the image quality of stylegan. In Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition (pp. 8110\u20138119). Piscataway: IEEE."},{"key":"86_CR81","first-page":"12863","volume-title":"Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition","author":"Z. Wu","year":"2021","unstructured":"Wu, Z., Lischinski, D., & Shechtman, E. (2021). Stylespace analysis: disentangled controls for stylegan image generation. In Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition (pp. 12863\u201312872). Piscataway: IEEE."},{"key":"86_CR82","first-page":"2256","volume-title":"Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition","author":"W. Xia","year":"2021","unstructured":"Xia, W., Yang, Y., Xue, J.-H., & Wu, B. (2021). TediGAN: text-guided diverse face image generation and manipulation. In Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition (pp. 2256\u20132265). Piscataway: IEEE."},{"key":"86_CR83","first-page":"18229","volume-title":"Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition","author":"Z. Xu","year":"2022","unstructured":"Xu, Z., Lin, T., Tang, H., Li, F., He, D., Sebe, N., Timofte, R., Van Gool, L., & Ding, E. (2022). Predict, prevent, and evaluate: disentangled text-driven image manipulation empowered by pre-trained vision-language model. In Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition (pp. 18229\u201318238). Piscataway: IEEE."},{"key":"86_CR84","first-page":"833","volume-title":"Proceedings of the 15th European conference on computer vision","author":"Y. Zhu","year":"2018","unstructured":"Zhu, Y., Papandreou, G., Schroff, F., Chen, L.-C., & Adam, H. (2018). Encoder-decoder with atrous separable convolution for semantic image segmentation. In V. Ferrari, M. Hebert, C. Sminchisescu, & Y. Weiss (Eds.), Proceedings of the 15th European conference on computer vision (pp. 833\u2013851). Cham: Springer."},{"key":"86_CR85","unstructured":"Shuai, X., Ding, H., Ma, X., Tu, R., Jiang, Y.-G., & Tao, D. (2024). A survey of multimodal-guided image editing with text-to-image diffusion models. arXiv preprint. arXiv:2406.14555."},{"key":"86_CR86","first-page":"1","volume-title":"Proceedings of the 11th international conference on learning representations","author":"G. Couairon","year":"2023","unstructured":"Couairon, G., Verbeek, J., Schwenk, H., & Cord, M. (2023). Diffedit: diffusion-based semantic image editing with mask guidance. In Proceedings of the 11th international conference on learning representations (pp. 1\u201321). OpenReview.net."},{"key":"86_CR87","first-page":"1","volume-title":"Proceedings of the 12th international conference on learning representations","author":"Q. Wang","year":"2023","unstructured":"Wang, Q., Zhang, B., Birsak, M., & Wonka, P. (2023). Instructedit: improving automatic masks for diffusion-based image editing with user instructions. In Proceedings of the 12th international conference on learning representations (pp. 1\u201319). OpenReview.net."},{"key":"86_CR88","first-page":"22560","volume-title":"Proceedings of the IEEE\/CVF international conference on computer vision","author":"M. Cao","year":"2023","unstructured":"Cao, M., Wang, X., Qi, Z., Shan, Y., Qie, X., & Zheng, Y. (2023). Masactrl: tuning-free mutual self-attention control for consistent image synthesis and editing. In Proceedings of the IEEE\/CVF international conference on computer vision (pp. 22560\u201322570). Piscataway: IEEE."},{"key":"86_CR89","unstructured":"Choi, J., Choi, Y., Kim, Y., Kim, J., & Yoon, S. (2023). Custom-edit: text-guided image editing with customized diffusion models. arXiv preprint. arXiv:2305.15779."},{"key":"86_CR90","first-page":"5220","volume-title":"Proceedings of the IEEE\/CVF winter conference on applications of computer vision","author":"Z. Zhang","year":"2024","unstructured":"Zhang, Z., Zheng, J., Fang, Z., & Plummer, B. A. (2024). Text-to-image editing by image information removal. In Proceedings of the IEEE\/CVF winter conference on applications of computer vision (pp. 5220\u20135229). Piscataway: IEEE."},{"key":"86_CR91","first-page":"16784","volume-title":"Proceedings of the 39th international conference on machine learning","author":"A. Q. Nichol","year":"2022","unstructured":"Nichol, A. Q., Dhariwal, P., Ramesh, A., Shyam, P., Mishkin, P., Mcgrew, B., Sutskever, I., & Chen, M. (2022). Glide: towards photorealistic image generation and editing with text-guided diffusion models. In K. Chaudhuri & S. Jegelka (Eds.), Proceedings of the 39th international conference on machine learning (pp. 16784\u201316804). PMLR."},{"key":"86_CR92","volume-title":"Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition","author":"O. Avrahami","year":"2022","unstructured":"Avrahami, O., Lischinski, D., & Fried, O. (2022). Blended diffusion for text-driven editing of natural images. In Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, Piscataway: IEEE."},{"key":"86_CR93","first-page":"4198","volume-title":"Proceedings of the IEEE\/CVF winter conference on applications of computer vision","author":"D. H. Park","year":"2024","unstructured":"Park, D. 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Piscataway: IEEE."},{"key":"86_CR96","first-page":"6027","volume-title":"Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition","author":"Z. Zhang","year":"2023","unstructured":"Zhang, Z., Han, L., Ghosh, A., Metaxas, D. N., & Sine, J. R. (2023). Single image editing with text-to-image diffusion models. In Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition (pp. 6027\u20136037). Piscataway: IEEE."},{"key":"86_CR97","first-page":"6007","volume-title":"Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition","author":"B. Kawar","year":"2023","unstructured":"Kawar, B., Zada, S., Lang, O., Tov, O., Chang, H., Dekel, T., Mosseri, I., & Irani, M. (2023). Imagic: text-based real image editing with diffusion models. In Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition (pp. 6007\u20136017). Piscataway: IEEE."},{"key":"86_CR98","doi-asserted-by":"crossref","unstructured":"Valevski, D., Kalman, M., Molad, E., Segalis, E., Matias, Y., & Leviathan, Y. (2023). Unitune: text-driven image editing by fine tuning a diffusion model on a single image. ACM Transactions on Graphics, 1\u201310.","DOI":"10.1145\/3592451"},{"key":"86_CR99","first-page":"1","volume-title":"Proceedings of the 10th international conference on learning representations","author":"A. Hertz","year":"2022","unstructured":"Hertz, A., Mokady, R., Tenenbaum, J., Aberman, K., Pritch, Y., & Cohen-Or, D. (2022). Prompt-to-prompt image editing with cross-attention control. In Proceedings of the 10th international conference on learning representations (pp. 1\u201319). OpenReview.net."},{"key":"86_CR100","unstructured":"Wang, Q., Zhang, B., Birsak, M., & Wonka, P. (2023). MDP: a generalized framework for text-guided image editing by manipulating the diffusion path. arXiv preprint. arXiv:2303.16765."},{"key":"86_CR101","first-page":"18392","volume-title":"Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition","author":"T. Brooks","year":"2023","unstructured":"Brooks, T., Holynski, A., & Efros, A. A. (2023). Instructpix2pix: learning to follow image editing instructions. In Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition (pp. 18392\u201318402). Piscataway: IEEE."},{"key":"86_CR102","first-page":"1921","volume-title":"Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition","author":"N. Tumanyan","year":"2023","unstructured":"Tumanyan, N., Geyer, M., Bagon, S., & Dekel, T. (2023). Plug-and-play diffusion features for text-driven image-to-image translation. In Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition (pp. 1921\u20131930). Piscataway: IEEE."},{"key":"86_CR103","first-page":"2426","volume-title":"Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition","author":"G. Kim","year":"2022","unstructured":"Kim, G., Kwon, T., & Ye, J. C. (2022). Diffusionclip: text-guided diffusion models for robust image manipulation. In Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition (pp. 2426\u20132435). Piscataway: IEEE."},{"key":"86_CR104","first-page":"1","volume-title":"Proceedings of the 11th international conference on learning representations","author":"G. Kwon","year":"2023","unstructured":"Kwon, G., & Ye, J. C. (2023). Diffusion-based image translation using disentangled style and content representation. In Proceedings of the 11th international conference on learning representations (pp. 1\u201322). OpenReview.net."},{"key":"86_CR105","doi-asserted-by":"crossref","unstructured":"Zeng, L., Zheng, Z., Wei, Y., & Chua, T. (2024). Instilling multi-round thinking to text-guided image generation. arXiv preprint. arXiv:2401.08472.","DOI":"10.2139\/ssrn.5152281"},{"key":"86_CR106","first-page":"13128","volume-title":"Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition","author":"C. Liu","year":"2024","unstructured":"Liu, C., Li, X., & Ding, H. (2024). Referring image editing: object-level image editing via referring expressions. In Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition (pp. 13128\u201313138). Piscataway: IEEE."},{"key":"86_CR107","first-page":"1","volume-title":"Proceedings of the 12th international conference on learning representations","author":"S. Liu","year":"2024","unstructured":"Liu, S., Zeng, Z., Ren, T., Li, F., Zhang, H., Yang, J., Li, C., Yang, J., Su, H., Zhu, J., et al. (2024). Grounding dino: marrying dino with grounded pre-training for open-set object detection. In Proceedings of the 12th international conference on learning representations (pp. 1\u201333). OpenReview.net."},{"key":"86_CR108","first-page":"4015","volume-title":"Proceedings of the IEEE\/CVF international conference on computer vision","author":"A. Kirillov","year":"2023","unstructured":"Kirillov, A., Mintun, E., Ravi, N., Mao, H., Rolland, C., Gustafson, L., Xiao, T., Whitehead, S., Berg, A. C., Lo, W.-Y., et al. (2023). Segment anything. In Proceedings of the IEEE\/CVF international conference on computer vision (pp. 4015\u20134026). Piscataway: IEEE."},{"key":"86_CR109","first-page":"10684","volume-title":"Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition","author":"R. Rombach","year":"2022","unstructured":"Rombach, R., Blattmann, A., Lorenz, D., Esser, P., & Ommer, B. (2022). High-resolution image synthesis with latent diffusion models. In Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition (pp. 10684\u201310695). Piscataway: IEEE."},{"key":"86_CR110","first-page":"6038","volume-title":"Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition","author":"R. Mokady","year":"2023","unstructured":"Mokady, R., Hertz, A., Aberman, K., Pritch, Y., & Cohen-Or, D. (2023). Null-text inversion for editing real images using guided diffusion models. In Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition (pp. 6038\u20136047). Piscataway: IEEE."},{"key":"86_CR111","first-page":"1","volume-title":"Proceedings of the 10th international conference on learning representations","author":"C. Meng","year":"2022","unstructured":"Meng, C., He, Y., Song, Y., Song, J., Wu, J., Zhu, J.-Y., & Ermon, S. (2022). SDEdit: guided image synthesis and editing with stochastic differential equations. In Proceedings of the 10th international conference on learning representations (pp. 1\u201333). OpenReview.net."},{"key":"86_CR112","first-page":"1877","volume-title":"Proceedings of the 34th international conference on neural information processing systems","author":"T. B. Brown","year":"2020","unstructured":"Brown, T. B., Mann, B., Ryder, N., Subbiah, M., Kaplan, J., Dhariwal, P., Neelakantan, A., Shyam, P., Sastry, G., Askell, A., et al. (2020). Language models are few-shot learners. In H. Larochelle, M. Ranzato, R. Hadsell, M. F. Balcan, & H. Lin (Eds.), Proceedings of the 34th international conference on neural information processing systems (pp. 1877\u20131901). Red Hook: Curran Associates."},{"issue":"1","key":"86_CR113","doi-asserted-by":"publisher","DOI":"10.1007\/s44267-024-00049-8","volume":"2","author":"C. Liu","year":"2024","unstructured":"Liu, C., Jiang, X., & Ding, H. (2024). Primitivenet: decomposing the global constraints for referring segmentation. Visual Intelligence, 2(1), 16.","journal-title":"Visual Intelligence"},{"key":"86_CR114","first-page":"23592","volume-title":"Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition","author":"C. Liu","year":"2023","unstructured":"Liu, C., Ding, H., & Jiang, X. (2023). Gres: generalized referring expression segmentation. In Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition (pp. 23592\u201323601). Piscataway: IEEE."},{"key":"86_CR115","first-page":"1140","volume-title":"Proceedings of the IEEE\/CVF winter conference on applications of computer vision","author":"M. U. Anwaar","year":"2021","unstructured":"Anwaar, M. U., Labintcev, E., & Kleinsteuber, M. (2021). Compositional learning of image-text query for image retrieval. In Proceedings of the IEEE\/CVF winter conference on applications of computer vision (pp. 1140\u20131149). 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New York: ACM."},{"key":"86_CR149","unstructured":"Yu, Y., Lee, S., Choi, Y., & Kim, G. (2020). CurlingNet: compositional learning between images and text for fashion IQ data. arXiv preprint. arXiv:2003.12299."},{"key":"86_CR150","unstructured":"Miech, A., Laptev, I., & Sivic, J. (2017). Learnable pooling with context gating for video classification. arXiv preprint. arXiv:1706.06905."},{"key":"86_CR151","first-page":"11307","volume-title":"Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition","author":"H. Wu","year":"2021","unstructured":"Wu, H., Gao, Y., Guo, X., Al-Halah, Z., Rennie, S., Grauman, K., & Feris, R. (2021). Fashion IQ: a new dataset towards retrieving images by natural language feedback. In Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition (pp. 11307\u201311317). Piscataway: IEEE."},{"key":"86_CR152","first-page":"6105","volume-title":"Proceedings of the 36th international conference on machine learning","author":"M. Tan","year":"2019","unstructured":"Tan, M., & Le, Q. (2019). EfficientNet: rethinking model scaling for convolutional neural networks. In Proceedings of the 36th international conference on machine learning (pp. 6105\u20136114). PMLR."},{"key":"86_CR153","first-page":"10972","volume-title":"Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition","author":"P. N. Chowdhury","year":"2023","unstructured":"Chowdhury, P. N., Bhunia, A. K., Sain, A., Koley, S., Xiang, T., & Song, Y.-Z. (2023). Scenetrilogy: on human scene-sketch and its complementarity with photo and text. In Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition (pp. 10972\u201310983). Piscataway: IEEE."},{"key":"86_CR154","unstructured":"Rossetto, L., Gasser, R., & Schuldt, H. (2019). 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Piscataway: IEEE."},{"key":"86_CR163","first-page":"1","volume-title":"Proceedings of the 2021 ACM on multimedia conference","author":"A. Baldrati","year":"2021","unstructured":"Baldrati, A., Bertini, M., Uricchio, T., & Del Bimbo, A. (2021). Conditioned image retrieval for fashion using contrastive learning and clip-based features. In Proceedings of the 2021 ACM on multimedia conference (pp. 1\u20135). New York: ACM."},{"key":"86_CR164","first-page":"1","volume-title":"Proceedings of the 12th international conference on learning representations","author":"S. Karthik","year":"2024","unstructured":"Karthik, S., Roth, K., Mancini, M., & Akata, Z. (2024). Vision-by-language for training-free compositional image retrieval. In Proceedings of the 12th international conference on learning representations (pp. 1\u201316). OpenReview.net."},{"key":"86_CR165","first-page":"1","volume":"2024","author":"G. Gu","year":"2024","unstructured":"Gu, G., Chun, S., Kim, W., Jun, H., Kang, Y., & Yun, S. 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Cham: Springer."},{"key":"86_CR168","first-page":"558","volume-title":"Proceedings of the 17th European conference on computer vision","author":"N. Cohen","year":"2022","unstructured":"Cohen, N., Gal, R., Meirom, E. A., Chechik, G., & Atzmon, Y. (2022). \u201cThis is my unicorn, fluffy\u201d: personalizing frozen vision-language representations. In S. Avidan, G. J. Brostow, M. Ciss\u00e9, G. M. Farinella, & T. Hassner (Eds.), Proceedings of the 17th European conference on computer vision (pp. 558\u2013577). Cham: Springer."},{"key":"86_CR169","doi-asserted-by":"publisher","first-page":"1012","DOI":"10.1145\/3477495.3532047","volume-title":"Proceedings of the 45th international ACM SIGIR conference on research and development in information retrieval","author":"Y. Zhao","year":"2022","unstructured":"Zhao, Y., Song, Y., & Jin, Q. (2022). Progressive learning for image retrieval with hybrid-modality queries. In Proceedings of the 45th international ACM SIGIR conference on research and development in information retrieval (pp. 1012\u20131021). New York: ACM."},{"key":"86_CR170","first-page":"19305","volume-title":"Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition","author":"K. Saito","year":"2023","unstructured":"Saito, K., Sohn, K., Zhang, X., Li, C.-L., Lee, C.-Y., Saenko, K., & Pfister, T. (2023). 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\u201319314). Piscataway: IEEE."},{"key":"86_CR171","first-page":"5180","volume-title":"Proceedings of the 38th AAAI conference on artificial intelligence","author":"Y. Tang","year":"2024","unstructured":"Tang, Y., Yu, J., Gai, K., Zhuang, J., Xiong, G., Hu, Y., & Wu, Q. (2024). Context-i2w: mapping images to context-dependent words for accurate zero-shot composed image retrieval. In Proceedings of the 38th AAAI conference on artificial intelligence (pp. 5180\u20135188). Palo Alto: AAAI."},{"key":"86_CR172","first-page":"26951","volume-title":"Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition","author":"Y. Suo","year":"2024","unstructured":"Suo, Y., Ma, F., Zhu, L., & Yang, Y. (2024). Knowledge-enhanced dual-stream zero-shot composed image retrieval. In Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition (pp. 26951\u201326962). Piscataway: IEEE."},{"key":"86_CR173","doi-asserted-by":"publisher","first-page":"978","DOI":"10.1145\/3652583.3658032","volume-title":"Proceedings of the 2024 international conference on multimedia retrieval","author":"H. Zhu","year":"2024","unstructured":"Zhu, H., Huang, J.-H., Rudinac, S., & Kanoulas, E. (2024). Enhancing interactive image retrieval with query rewriting using large language models and vision language models. In Proceedings of the 2024 international conference on multimedia retrieval (pp. 978\u2013987). New York: ACM."},{"key":"86_CR174","first-page":"16509","volume-title":"Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition","author":"S. Koley","year":"2024","unstructured":"Koley, S., Bhunia, A. K., Sain, A., Chowdhury, P. N., Xiang, T., & Song, Y.-Z. (2024). You\u2019ll never walk alone: a sketch and text duet for fine-grained image retrieval. In Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition (pp. 16509\u201316519). Piscataway: IEEE."},{"key":"86_CR175","doi-asserted-by":"publisher","first-page":"229","DOI":"10.1145\/3626772.3657727","volume-title":"Proceedings of the 47th international ACM SIGIR conference on research and development in information retrieval","author":"H. Wen","year":"2024","unstructured":"Wen, H., Song, X., Chen, X., Wei, Y., Nie, L., & Chua, T.-S. (2024). Simple but effective raw-data level multimodal fusion for composed image retrieval. In Proceedings of the 47th international ACM SIGIR conference on research and development in information retrieval (pp. 229\u2013239). New York: ACM."},{"key":"86_CR176","first-page":"387","volume-title":"Proceedings of the 18th European conference on computer vision","author":"C. Wei","year":"2024","unstructured":"Wei, C., Chen, Y., Chen, H., Hu, H., Zhang, G., Fu, J., Ritter, A., & Chen, W. (2024). UniIR: training and benchmarking universal multimodal information retrievers. In A. Leonardis, E. Ricci, S. Roth, O. Russakovsky, T. Sattler, & G. Varol (Eds.), Proceedings of the 18th European conference on computer vision (pp. 387\u2013404). Cham: Springer."},{"key":"86_CR177","first-page":"15338","volume-title":"Proceedings of the IEEE\/CVF international conference on computer vision","author":"A. Baldrati","year":"2023","unstructured":"Baldrati, A., Agnolucci, L., Bertini, M., & Del Bimbo, A. (2023). Zero-shot composed image retrieval with textual inversion. In Proceedings of the IEEE\/CVF international conference on computer vision (pp. 15338\u201315347). Piscataway: IEEE."},{"key":"86_CR178","volume-title":"Proceedings of the 41st international conference on machine learning","author":"K. Zhang","year":"2024","unstructured":"Zhang, K., Luan, Y., Hu, H., Lee, K., Qiao, S., Chen, W., Su, Y., & Chang, M.-W. (2024). Magiclens: self-supervised image retrieval with open-ended instructions. In Proceedings of the 41st international conference on machine learning. Vienna: PMLR."},{"key":"86_CR179","first-page":"1201","volume-title":"Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition","author":"O. Barbany","year":"2024","unstructured":"Barbany, O., Huang, M., Zhu, X., & Dhua, A. (2024). Leveraging large language models for multimodal search. In Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition (pp. 1201\u20131210). Piscataway: IEEE."},{"key":"86_CR180","unstructured":"Chen, J., & Lai, H. (2023). Ranking-aware uncertainty for text-guided image retrieval. arXiv preprint. arXiv:2308.08131."},{"key":"86_CR181","unstructured":"Chen, J., & Lai, H. (2023). Pretrain like you inference: masked tuning improves zero-shot composed image retrieval. arXiv preprint. arXiv:2311.07622."},{"key":"86_CR182","first-page":"13225","volume-title":"Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition","author":"G. Gu","year":"2024","unstructured":"Gu, G., Chun, S., Kim, W., Kang, Y., & Yun, S. (2024). Language-only efficient training of zero-shot composed image retrieval. In Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition (pp. 13225\u201313234). Piscataway: IEEE."},{"key":"86_CR183","first-page":"6104","volume-title":"Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition","author":"F. 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ImageNet classification with deep convolutional neural networks. In F. Pereira, C. J. C. Burges, L. Bottou, & K. Q. Weinberger (Eds.), Proceedings of the 26th international conference on neural information processing systems (pp. 84\u201390). Red Hook: Curran Associates."},{"key":"86_CR186","first-page":"584","volume-title":"Proceedings of the 13th European conference on computer vision","author":"A. Babenko","year":"2014","unstructured":"Babenko, A., Slesarev, A., Chigorin, A., & Lempitsky, V. (2014). Neural codes for image retrieval. In D. J. Fleet, T. Pajdla, B. Schiele, & T. Tuytelaars (Eds.), Proceedings of the 13th European conference on computer vision (pp. 584\u2013599). Cham: Springer."},{"key":"86_CR187","first-page":"1","volume-title":"Proceedings of the 3th international conference on learning representations","author":"K. Simonyan","year":"2015","unstructured":"Simonyan, K., & Zisserman, A. (2015). Very deep convolutional networks for large-scale image recognition. In Proceedings of the 3th international conference on learning representations (pp. 1\u201314). OpenReview.net."},{"key":"86_CR188","first-page":"4700","volume-title":"Proceedings of the IEEE conference on computer vision and pattern recognition","author":"G. Huang","year":"2017","unstructured":"Huang, G., Liu, Z., Van Der Maaten, L., & Weinberger, K. Q. (2017). Densely connected convolutional networks. In Proceedings of the IEEE conference on computer vision and pattern recognition (pp. 4700\u20134708). Piscataway: IEEE."},{"key":"86_CR189","first-page":"1","volume-title":"Proceedings of the IEEE conference on computer vision and pattern recognition","author":"C. Szegedy","year":"2015","unstructured":"Szegedy, C., Liu, W., Jia, Y., Sermanet, P., Reed, S., Anguelov, D., Erhan, D., Vanhoucke, V., & Rabinovich, A. (2015). Going deeper with convolutions. In Proceedings of the IEEE conference on computer vision and pattern recognition (pp. 1\u20139). Piscataway: IEEE."},{"key":"86_CR190","unstructured":"Howard, A. G., Zhu, M., Chen, B., Kalenichenko, D., Wang, W., Weyand, T., Andreetto, M., & Adam, H. (2017). MobileNets: efficient convolutional neural networks for mobile vision applications. arXiv preprint. arXiv:1704.04861."},{"key":"86_CR191","first-page":"1386","volume-title":"Proceedings of the IEEE conference on computer vision and pattern recognition","author":"J. Wang","year":"2014","unstructured":"Wang, J., Song, Y., Leung, T., Rosenberg, C., Wang, J., Philbin, J., Chen, B., & Wu, Y. (2014). Learning fine-grained image similarity with deep ranking. In Proceedings of the IEEE conference on computer vision and pattern recognition (pp. 1386\u20131393). Piscataway: IEEE."},{"key":"86_CR192","first-page":"770","volume-title":"Proceedings of the IEEE conference on computer vision and pattern recognition","author":"K. He","year":"2016","unstructured":"He, K., Zhang, X., Ren, S., & Sun, J. (2016). Deep residual learning for image recognition. In Proceedings of the IEEE conference on computer vision and pattern recognition (pp. 770\u2013778). Piscataway: IEEE."},{"key":"86_CR193","doi-asserted-by":"publisher","first-page":"1208","DOI":"10.1145\/3404835.3462971","volume-title":"Proceedings of the 44th international ACM SIGIR conference on research and development in information retrieval","author":"F. Feng","year":"2021","unstructured":"Feng, F., Huang, W., He, X., Xin, X., Wang, Q., & Chua, T.-S. (2021). Should graph convolution trust neighbors? A simple causal inference method. In Proceedings of the 44th international ACM SIGIR conference on research and development in information retrieval (pp. 1208\u20131218). New York: ACM."},{"issue":"06","key":"86_CR194","doi-asserted-by":"publisher","first-page":"2493","DOI":"10.1109\/TKDE.2019.2957786","volume":"33","author":"F. Feng","year":"2019","unstructured":"Feng, F., He, X., Tang, J., & Chua, T.-S. (2019). 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In Proceedings of the 2019 ACM on multimedia conference (pp. 1437\u20131445). New York: ACM."},{"issue":"1","key":"86_CR197","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3425636","volume":"17","author":"X. Yang","year":"2021","unstructured":"Yang, X., Song, X., Feng, F., Wen, H., Duan, L.-Y., & Nie, L. (2021). Attribute-wise explainable fashion compatibility modeling. ACM Transactions on Multimedia Computing Communications and Applications, 17(1), 1\u201321.","journal-title":"ACM Transactions on Multimedia Computing Communications and Applications"},{"key":"86_CR198","first-page":"1137","volume-title":"Proceedings of the 29th international conference on neural information processing systems","author":"S. Ren","year":"2015","unstructured":"Ren, S., He, K., Girshick, R., & Sun, J. (2015). Faster R-CNN: towards real-time object detection with region proposal networks. In C. Cortes, N. Lawrence, D. Lee, M. Sugiyama, & R. Garnett (Eds.), Proceedings of the 29th international conference on neural information processing systems (pp. 1137\u20131149). Red Hook: Curran Associates."},{"key":"86_CR199","first-page":"2547","volume-title":"Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition","author":"L. Zhang","year":"2019","unstructured":"Zhang, L., Qi, G.-J., Wang, L., & Luo, J. (2019). AET vs. AED: unsupervised representation learning by auto-encoding transformations rather than data. In Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition (pp. 2547\u20132555). Piscataway: IEEE."},{"key":"86_CR200","first-page":"3367","volume-title":"Proceedings of the 2020 ACM on multimedia conference","author":"F. Zhang","year":"2020","unstructured":"Zhang, F., Xu, M., Mao, Q., & Xu, C. (2020). Joint attribute manipulation and modality alignment learning for composing text and image to image retrieval. In Proceedings of the 2020 ACM on multimedia conference (pp. 3367\u20133376). New York: ACM."},{"key":"86_CR201","first-page":"121","volume-title":"Proceedings of the 16th European conference on computer vision","author":"X. Li","year":"2020","unstructured":"Li, X., Yin, X., Li, C., Zhang, P., Hu, X., Zhang, L., Wang, L., Hu, H., Dong, L., Wei, F., et al. (2020). Oscar: object-semantics aligned pre-training for vision-language tasks. In A. Vedaldi, H. Bischof, T. Brox, & J.-M. Frahm (Eds.), Proceedings of the 16th European conference on computer vision (pp. 121\u2013137). Cham: Springer."},{"issue":"13","key":"86_CR202","doi-asserted-by":"publisher","first-page":"18713","DOI":"10.1007\/s11042-018-7148-1","volume":"78","author":"R. Furuta","year":"2019","unstructured":"Furuta, R., Inoue, N., & Yamasaki, T. (2019). Efficient and interactive spatial-semantic image retrieval. Multimedia Tools and Applications, 78(13), 18713\u201318733.","journal-title":"Multimedia Tools and Applications"},{"key":"86_CR203","unstructured":"Jandial, S., Chopra, A., Badjatiya, P., Chawla, P., Sarkar, M., & Trace, B. K. (2020). Transform aggregate and compose visiolinguistic representations for image search with text feedback. arXiv preprint. arXiv:2009.01485."},{"issue":"1","key":"86_CR204","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3284750","volume":"15","author":"Y. Peng","year":"2019","unstructured":"Peng, Y., & Qi, J. (2019). CM-GANs: cross-modal generative adversarial networks for common representation learning. ACM Transactions on Multimedia Computing Communications and Applications, 15(1), 1\u201324.","journal-title":"ACM Transactions on Multimedia Computing Communications and Applications"},{"key":"86_CR205","first-page":"5998","volume-title":"Proceedings of the 31st international conference on neural information processing systems","author":"A. 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OpenReview.net."},{"key":"86_CR207","first-page":"4015","volume-title":"Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition","author":"Y. Liu","year":"2024","unstructured":"Liu, Y., Chen, P., Cai, J., Jiang, X., Hu, Y., Yao, J., Wang, Y., & Xie, W. (2024). LamRA: large multimodal model as your advanced retrieval assistant. In Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition (pp. 4015\u20134025). Piscataway: IEEE."},{"key":"86_CR208","first-page":"2556","volume-title":"Proceedings of the Association for Computational Linguistics","author":"P. Sharma","year":"2018","unstructured":"Sharma, P., Ding, N., Goodman, S., & Soricut, R. (2018). Conceptual captions: a cleaned, hypernymed, image alt-text dataset for automatic image captioning. In Proceedings of the Association for Computational Linguistics (pp. 2556\u20132565). Stroudsburg: ACL."},{"key":"86_CR209","unstructured":"Schuhmann, C., Vencu, R., Beaumont, R., Kaczmarczyk, R., Mullis, C., Katta, A., Coombes, T., Jitsev, J., & Komatsuzaki, A. (2021). Laion-400m: open dataset of clip-filtered 400 million image-text pairs. arXiv preprint. arXiv:2111.02114."},{"key":"86_CR210","first-page":"49250","volume-title":"Proceedings of the 37th international conference on neural information processing systems","author":"W. Dai","year":"2023","unstructured":"Dai, W., Li, J., Li, D., Tiong, A., Zhao, J., Wang, W., Li, B., Fung, P., & Hoi, S. (2023). InstructBLIP: towards general-purpose vision-language models with instruction tuning. In A. Oh, T. Neumann, A. Globerson, K. Saenko, M. Hardt, & S. Levine (Eds.), Proceedings of the 37th international conference on neural information processing systems (pp. 49250\u201349267). Red Hook: Curran Associates."},{"key":"86_CR211","first-page":"6595","volume-title":"Proceedings of the 37th international conference on neural information processing systems","author":"L. Zheng","year":"2023","unstructured":"Zheng, L., Chiang, W.-L., Sheng, Y., Zhuang, S., Wu, Z., Zhuang, Y., Lin, Z., Li, Z., Li, D., Xing, E., et al. (2023). Judging LLM-as-a-judge with MT-bench and chatbot arena. In A. Oh, T. Neumann, A. Globerson, K. Saenko, M. Hardt, & S. Levine (Eds.), Proceedings of the 37th international conference on neural information processing systems (pp. 6595\u201346623). Red Hook: Curran Associates."},{"key":"86_CR212","first-page":"12136","volume-title":"Proceedings of the IEEE\/CVF international conference on computer vision","author":"S. Changpinyo","year":"2021","unstructured":"Changpinyo, S., Pont-Tuset, J., Ferrari, V., & Soricut, R. (2021). Telling the what while pointing to the where: multimodal queries for image retrieval. In Proceedings of the IEEE\/CVF international conference on computer vision (pp. 12136\u201312146). Piscataway: IEEE."},{"key":"86_CR213","first-page":"131","volume-title":"Proceedings of the IEEE international conference on acoustics, speech and signal processing","author":"S. Hershey","year":"2017","unstructured":"Hershey, S., Chaudhuri, S., Ellis, D. P. W., Gemmeke, J. F., Jansen, A., Moore, R. C., Plakal, M., Platt, D., Saurous, R. A., Seybold, B., et al. (2017). CNN architectures for large-scale audio classification. In Proceedings of the IEEE international conference on acoustics, speech and signal processing (pp. 131\u2013135). Piscataway: IEEE."},{"key":"86_CR214","unstructured":"Sanh, V., Debut, L., Chaumond, J., & Wolf, T. (2019). Distilbert, a distilled version of bert: smaller, faster, cheaper and lighter. arXiv preprint. arXiv:1910.01108."},{"key":"86_CR215","first-page":"358","volume-title":"Proceedings of the 17th European conference on computer vision","author":"G. Tevet","year":"2022","unstructured":"Tevet, G., Gordon, B., Hertz, A., Bermano, A. H., & Cohen-Or, D. (2022). Motionclip: exposing human motion generation to clip space. In S. Avidan, G. J. Brostow, M. Ciss\u00e9, G. M. Farinella, & T. Hassner (Eds.), Proceedings of the 17th European conference on computer vision (pp. 358\u2013374). Cham: Springer."},{"key":"86_CR216","first-page":"5815","volume-title":"Proceedings of the IEEE\/CVF winter conference on applications of computer vision","author":"Y. Ruan","year":"2024","unstructured":"Ruan, Y., Lee, H.-H., Zhang, Y., Zhang, K., & Chang, A. X. (2024). Tricolo: trimodal contrastive loss for text to shape retrieval. In Proceedings of the IEEE\/CVF winter conference on applications of computer vision (pp. 5815\u20135825). Piscataway: IEEE."},{"issue":"2","key":"86_CR217","doi-asserted-by":"publisher","first-page":"481","DOI":"10.1109\/TNNLS.2020.2980129","volume":"32","author":"Y. 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Zhang","year":"2024","unstructured":"Zhang, N., Liu, Y., Li, Z., Xiang, J., & Pan, R. (2024). Fabric image retrieval based on multi-modal feature fusion. Signal, Image and Video Processing, 18(3), 2207\u20132217.","journal-title":"Signal, Image and Video Processing"},{"key":"86_CR220","first-page":"1200","volume-title":"Proceedings of the 12th international conference on document analysis and recognition","author":"E. Hassan","year":"2013","unstructured":"Hassan, E., Chaudhury, S., & Gopal, M. (2013). Multi-modal information integration for document retrieval. In Proceedings of the 12th international conference on document analysis and recognition (pp. 1200\u20131204). Piscataway: IEEE."},{"key":"86_CR221","first-page":"776","volume-title":"Proceedings of the IEEE international conference on acoustics, speech and signal processing","author":"J. F. Gemmeke","year":"2017","unstructured":"Gemmeke, J. F., Ellis, D. P. W., Freedman, D., Jansen, A., Lawrence, W., Moore, R. C., Plakal, M., & Ritter, M. (2017). Audio set: an ontology and human-labeled dataset for audio events. In Proceedings of the IEEE international conference on acoustics, speech and signal processing (pp. 776\u2013780). Piscataway: IEEE."},{"key":"86_CR222","first-page":"647","volume-title":"Proceedings of the 16th European conference on computer vision","author":"J. Pont-Tuset","year":"2020","unstructured":"Pont-Tuset, J., Uijlings, J., Changpinyo, S., Soricut, R., & Ferrari, V. (2020). Connecting vision and language with localized narratives. In A. Vedaldi, H. Bischof, T. Brox, & J.-M. Frahm (Eds.), Proceedings of the 16th European conference on computer vision (pp. 647\u2013664). Cham: Springer."},{"key":"86_CR223","unstructured":"Wah, C., Branson, S., Welinder, P., Perona, P., & Belongie, S. (2011). The caltech-ucsd birds-200-2011 dataset. Technical report, California Institute of Technology."},{"key":"86_CR224","first-page":"722","volume-title":"Proceedings of the 6th Indian conference on computer vision, graphics & image processing","author":"M.-E. Nilsback","year":"2008","unstructured":"Nilsback, M.-E., & Zisserman, A. (2008). Automated flower classification over a large number of classes. In Proceedings of the 6th Indian conference on computer vision, graphics & image processing (pp. 722\u2013729). Piscataway: IEEE."},{"key":"86_CR225","first-page":"3730","volume-title":"Proceedings of the IEEE international conference on computer vision","author":"Z. Liu","year":"2015","unstructured":"Liu, Z., Luo, P., Wang, X., & Tang, X. (2015). Deep learning face attributes in the wild. In Proceedings of the IEEE international conference on computer vision (pp. 3730\u20133738). Piscataway: IEEE."},{"key":"86_CR226","first-page":"1680","volume-title":"Proceedings of the IEEE international conference on computer vision","author":"S. Zhu","year":"2017","unstructured":"Zhu, S., Urtasun, R., Fidler, S., Lin, D., & Loy, C. C. (2017). Be your own prada: fashion synthesis with structural coherence. In Proceedings of the IEEE international conference on computer vision (pp. 1680\u20131688). Piscataway: IEEE."},{"key":"86_CR227","first-page":"97","volume-title":"Proceedings of the IEEE conference on computer vision and pattern recognition","author":"V. Bychkovsky","year":"2011","unstructured":"Bychkovsky, V., Paris, S., Chan, E., & Durand, F. (2011). Learning photographic global tonal adjustment with a database of input\/output image pairs. In Proceedings of the IEEE conference on computer vision and pattern recognition (pp. 97\u2013104). Piscataway: IEEE."},{"key":"86_CR228","first-page":"740","volume-title":"Proceedings of the 13th European conference on computer vision","author":"T.-Y. Lin","year":"2014","unstructured":"Lin, T.-Y., Maire, M., Belongie, S., Hays, J., Perona, P., Ramanan, D., Doll\u00e1r, P., & Zitnick, C. L. (2014). Microsoft coco: common objects in context. In D. J. Fleet, T. Pajdla, B. Schiele, & T. Tuytelaars (Eds.), Proceedings of the 13th European conference on computer vision (pp. 740\u2013755). Cham: Springer."},{"key":"86_CR229","first-page":"787","volume-title":"Proceedings of the 2014 conference on empirical methods in natural language processing","author":"S. Kazemzadeh","year":"2014","unstructured":"Kazemzadeh, S., Ordonez, V., Matten, M., & Berg, T. (2014). ReferItGame: referring to objects in photographs of natural scenes. In A. Moschitti, B. Pang, & W. Daelemans (Eds.), Proceedings of the 2014 conference on empirical methods in natural language processing (pp. 787\u2013798). Stroudsburg: ACL."},{"key":"86_CR230","first-page":"2901","volume-title":"Proceedings of the IEEE conference on computer vision and pattern recognition","author":"J. Johnson","year":"2017","unstructured":"Johnson, J., Hariharan, B., Van Der Maaten, L., Li, F.-F., Zitnick, C. L., & Girshick, R. (2017). 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\u20132910). Piscataway: IEEE."},{"key":"86_CR231","doi-asserted-by":"publisher","first-page":"6495","DOI":"10.18653\/v1\/P19-1651","volume-title":"Proceedings of the 57th annual meeting of the Association for Computational Linguistics","author":"J.-H. Kim","year":"2019","unstructured":"Kim, J.-H., Kitaev, N., Chen, X., Rohrbach, M., Zhang, B.-T., Tian, Y., Batra, D., & Parikh, D. (2019). Codraw: collaborative drawing as a testbed for grounded goal-driven communication. In Proceedings of the 57th annual meeting of the Association for Computational Linguistics (pp. 6495\u20136513). Stroudsburg: ACL."},{"key":"86_CR232","first-page":"3213","volume-title":"Proceedings of the IEEE conference on computer vision and pattern recognition","author":"M. Cordts","year":"2016","unstructured":"Cordts, M., Omran, M., Ramos, S., Rehfeld, T., Enzweiler, M., Benenson, R., Franke, U., Roth, S., & Schiele, B. (2016). The cityscapes dataset for semantic urban scene understanding. In Proceedings of the IEEE conference on computer vision and pattern recognition (pp. 3213\u20133223). Piscataway: IEEE."},{"key":"86_CR233","unstructured":"Yu, F., Seff, A., Zhang, Y., Song, S., Funkhouser, T., & Lsun, J. X. (2015). Construction of a large-scale image dataset using deep learning with humans in the loop. arXiv preprint. arXiv:1506.03365."},{"key":"86_CR234","first-page":"8188","volume-title":"Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition","author":"Y. Choi","year":"2020","unstructured":"Choi, Y., Uh, Y., Yoo, J., & Ha, J.-W. (2020). Stargan v2: diverse image synthesis for multiple domains. In Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition (pp. 8188\u20138197). Piscataway: IEEE."},{"key":"86_CR235","first-page":"1","volume-title":"Proceedings of the 6th international conference on learning representations","author":"T. Karras","year":"2018","unstructured":"Karras, T., Aila, T., Laine, S., & Lehtinen, J. (2018). Progressive growing of GANs for improved quality, stability, and variation. In Proceedings of the 6th international conference on learning representations (pp. 1\u201326). OpenReview.net."},{"issue":"7","key":"86_CR236","doi-asserted-by":"publisher","first-page":"1354","DOI":"10.1109\/TPAMI.2011.227","volume":"34","author":"Z. Si","year":"2012","unstructured":"Si, Z., & Zhu, S.-C. (2012). Learning hybrid image templates (HIT) by information projection. IEEE Transactions on Pattern Analysis and Machine Intelligence, 34(7), 1354\u20131367.","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"86_CR237","first-page":"9465","volume-title":"Proceedings of the IEEE conference on computer vision and pattern recognition","author":"Y. Chen","year":"2018","unstructured":"Chen, Y., Lai, Y.-K., & Cartoongan, Y.-J. L. (2018). Generative adversarial networks for photo cartoonization. In Proceedings of the IEEE conference on computer vision and pattern recognition (pp. 9465\u20139474). 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