{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,3]],"date-time":"2026-08-03T06:43:57Z","timestamp":1785739437871,"version":"3.56.0"},"publisher-location":"Cham","reference-count":35,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031915840","type":"print"},{"value":"9783031915857","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025]]},"DOI":"10.1007\/978-3-031-91585-7_1","type":"book-chapter","created":{"date-parts":[[2025,5,27]],"date-time":"2025-05-27T08:45:54Z","timestamp":1748335554000},"page":"1-16","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Revisiting Relevance Feedback for\u00a0CLIP-Based Interactive Image Retrieval"],"prefix":"10.1007","author":[{"given":"Ryoya","family":"Nara","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yu-Chieh","family":"Lin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuji","family":"Nozawa","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Youyang","family":"Ng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Goh","family":"Itoh","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Osamu","family":"Torii","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yusuke","family":"Matsui","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,5,12]]},"reference":[{"key":"1_CR1","doi-asserted-by":"crossref","unstructured":"Ahmed, A.: Implementing relevance feedback for content-based medical image retrieval. IEEE Access (2020)","DOI":"10.1109\/ACCESS.2020.2990557"},{"key":"1_CR2","doi-asserted-by":"crossref","unstructured":"Anwaar, M.U., Labintcev, E., Kleinsteuber, M.: Compositional learning of image-text query for image retrieval. In: WACV (2021)","DOI":"10.1109\/WACV48630.2021.00118"},{"key":"1_CR3","doi-asserted-by":"crossref","unstructured":"Anwaar, M.U., Labintcev, E., Kleinsteuber, M.: Compositional learning of image-text query for image retrieval. In: WACV (2021)","DOI":"10.1109\/WACV48630.2021.00118"},{"key":"1_CR4","unstructured":"Chang, Y., Cirillo, C., Razon, J.: Evaluation of feedback retrieval using modified freezing, residual collection and test and control groups. The SMART retrieval system-experiments in automatic document processing (1971)"},{"key":"1_CR5","doi-asserted-by":"crossref","unstructured":"Chen, W., Chen, X., Zhang, J., Huang, K.: Beyond triplet loss: a deep quadruplet network for person re-identification. In: CVPR (2017)","DOI":"10.1109\/CVPR.2017.145"},{"key":"1_CR6","doi-asserted-by":"crossref","unstructured":"Han, X., et al.: Automatic spatially-aware fashion concept discovery. In: ICCV (2017)","DOI":"10.1109\/ICCV.2017.163"},{"key":"1_CR7","doi-asserted-by":"crossref","unstructured":"Harman, D.: Relevance feedback revisited. In: ACM SIGIR (1992)","DOI":"10.1145\/133160.133167"},{"key":"1_CR8","doi-asserted-by":"crossref","unstructured":"Hoffer, E., Ailon, N.: Deep metric learning using triplet network (2014)","DOI":"10.1007\/978-3-319-24261-3_7"},{"key":"1_CR9","doi-asserted-by":"crossref","unstructured":"Hull, D.: Using statistical testing in the evaluation of retrieval experiments. In: ACM SIGIR (1993)","DOI":"10.1145\/160688.160758"},{"key":"1_CR10","doi-asserted-by":"crossref","unstructured":"Isola, P., Lim, J.J., Adelson, E.H.: Discovering states and transformations in image collections. In: CVPR (2015)","DOI":"10.1109\/CVPR.2015.7298744"},{"key":"1_CR11","doi-asserted-by":"crossref","unstructured":"Kim, S., Kim, D., Cho, M., Kwak, S.: Proxy anchor loss for deep metric learning. In: CVPR (2020)","DOI":"10.1109\/CVPR42600.2020.00330"},{"key":"1_CR12","unstructured":"Kirillov, A., Lin, T.Y., Caesar, H., Girshick, R., Doll\u00e1\u2019r, P.: Microsoft COCO: Panoptic segmentation challenge (2017)"},{"key":"1_CR13","doi-asserted-by":"crossref","unstructured":"Krause, J., Stark, M., Deng, J., Fei-Fei, L.: 3D object representations for fine-grained categorization. In: ICCVW (2013)","DOI":"10.1109\/ICCVW.2013.77"},{"key":"1_CR14","doi-asserted-by":"crossref","unstructured":"Lim, J., Yun, S., Park, S., Choi, J.Y.: Hypergraph-induced semantic tuplet loss for deep metric learning. In: CVPR (2022)","DOI":"10.1109\/CVPR52688.2022.00031"},{"key":"1_CR15","doi-asserted-by":"crossref","unstructured":"Lin, T.Y., et al.: Microsoft COCO: common objects in context. In: ECCV (2014)","DOI":"10.1007\/978-3-319-10602-1_48"},{"key":"1_CR16","doi-asserted-by":"crossref","unstructured":"Meng, Q., Zhao, S., Huang, Z., Zhou, F.: MagFace: a universal representation for face recognition and quality assessment. In: CVPR (2021)","DOI":"10.1109\/CVPR46437.2021.01400"},{"key":"1_CR17","unstructured":"Mokady, R., Hertz, A., Bermano, A.H.: ClipCap: Clip prefix for image captioning. arXiv preprint arXiv:2111.09734 (2021)"},{"key":"1_CR18","doi-asserted-by":"crossref","unstructured":"Movshovitz-Attias, Y., Toshev, A., Leung, T.K., Ioffe, S., Singh, S.: No fuss distance metric learning using proxies. In: ICCV (2017)","DOI":"10.1109\/ICCV.2017.47"},{"key":"1_CR19","doi-asserted-by":"crossref","unstructured":"Musgrave, K., Belongie, S.J., Lim, S.N.: A metric learning reality check. In: ECCV (2020)","DOI":"10.1007\/978-3-030-58595-2_41"},{"key":"1_CR20","doi-asserted-by":"crossref","unstructured":"Nakata, K., Ng, Y., Miyashita, D., Maki, A., Lin, Y.C., Deguchi, J.: Revisiting a KNN-based image classification system with high-capacity storage. In: ECCV (2022)","DOI":"10.1007\/978-3-031-19836-6_26"},{"key":"1_CR21","unstructured":"Radford, A., et al.: Learning transferable visual models from natural language supervision. In: ICML (2021)"},{"key":"1_CR22","doi-asserted-by":"crossref","unstructured":"Rastegar, H., Giveki, D.: Designing a new deep convolutional neural network for content-based image retrieval with relevance feedback. Comput. Electr. Eng. (2023)","DOI":"10.2139\/ssrn.4102580"},{"key":"1_CR23","unstructured":"Rui, Y., Huang, T., Ortega, M., Mehrotra, S.: Relevance feedback: a power tool for interactive content-based image retrieval. IEEE TCSVT (1998)"},{"key":"1_CR24","volume-title":"CLIP for All Things Zero-Shot Sketch-Based Image Retrieval","author":"A Sain","year":"2023","unstructured":"Sain, A., Bhunia, A.K., Chowdhury, P.N., Koley, S., Xiang, T., Song, Y.Z.: CLIP for All Things Zero-Shot Sketch-Based Image Retrieval. CVPR, Fine-Grained or Not. In (2023)"},{"key":"1_CR25","doi-asserted-by":"crossref","unstructured":"Saito, K., et al.: Pic2Word: mapping pictures to words for zero-shot composed image retrieval. In: CVPR (2023)","DOI":"10.1109\/CVPR52729.2023.01850"},{"key":"1_CR26","doi-asserted-by":"crossref","unstructured":"Vaze, S., Carion, N., Misra, I.: GeneCIS: a benchmark for general conditional image similarity. In: CVPR (2023)","DOI":"10.1109\/CVPR52729.2023.00663"},{"key":"1_CR27","doi-asserted-by":"publisher","DOI":"10.1145\/3528223.3530068","volume-title":"Clipasso: Semantically-Aware Object Sketching","author":"Y Vinker","year":"2022","unstructured":"Vinker, Y., et al.: Clipasso: Semantically-Aware Object Sketching. ACM Trans, Graph (2022)"},{"key":"1_CR28","doi-asserted-by":"crossref","unstructured":"Vo, N., et al.: Composing text and image for image retrieval - an empirical odyssey. In: CVPR (2019)","DOI":"10.1109\/CVPR.2019.00660"},{"key":"1_CR29","doi-asserted-by":"crossref","unstructured":"Wang, X., Han, X., Huang, W., Dong, D., Scott, M.R.: Multi-similarity loss with general pair weighting for deep metric learning. In: CVPR (2019)","DOI":"10.1109\/CVPR.2019.00516"},{"key":"1_CR30","unstructured":"Wang, Z., Wu, Y.: Click-feedback retrieval (2023)"},{"key":"1_CR31","unstructured":"Weinberger, K.Q., Blitzer, J., Saul, L.: Distance metric learning for large margin nearest neighbor classification. In: NIPS (2005)"},{"key":"1_CR32","unstructured":"Welinder, P., et al.: Caltech-UCSD birds 200 (2010)"},{"key":"1_CR33","doi-asserted-by":"crossref","unstructured":"Wertheimer, D., Tang, L., Hariharan, B.: Few-shot classification with feature map reconstruction networks. In: CVPR (2021)","DOI":"10.1109\/CVPR46437.2021.00792"},{"key":"1_CR34","doi-asserted-by":"crossref","unstructured":"Weyand, T., Araujo, A., Cao, B., Sim, J.: Google landmarks dataset v2 - a large-scale benchmark for instance-level recognition and retrieval. In: CVPR (2020)","DOI":"10.1109\/CVPR42600.2020.00265"},{"key":"1_CR35","unstructured":"Wu, H., Lu, H., Ma, S.: WillHunter: interactive image retrieval with multilevel relevance. In: ICPR (2004)"}],"container-title":["Lecture Notes in Computer Science","Computer Vision \u2013 ECCV 2024 Workshops"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-91585-7_1","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,5,27]],"date-time":"2025-05-27T08:46:22Z","timestamp":1748335582000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-91585-7_1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"ISBN":["9783031915840","9783031915857"],"references-count":35,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-91585-7_1","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025]]},"assertion":[{"value":"12 May 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ECCV","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"European Conference on Computer Vision","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Milan","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Italy","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"29 September 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"4 October 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"eccv2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/eccv2024.ecva.net\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}