{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,15]],"date-time":"2026-06-15T15:55:24Z","timestamp":1781538924575,"version":"3.54.5"},"publisher-location":"New York, NY, USA","reference-count":51,"publisher":"ACM","license":[{"start":{"date-parts":[[2026,6,15]],"date-time":"2026-06-15T00:00:00Z","timestamp":1781481600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2026,6,16]]},"DOI":"10.1145\/3805622.3810838","type":"proceedings-article","created":{"date-parts":[[2026,6,15]],"date-time":"2026-06-15T14:42:57Z","timestamp":1781534577000},"page":"177-185","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["RFHNet: Relational and Frequency-Aware Hashing Network for Large-Scale Fine-Grained Food Image Retrieval"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0008-8886-5530","authenticated-orcid":false,"given":"Junsong","family":"Wang","sequence":"first","affiliation":[{"name":"School of Computer Science and Artificial Intelligence, Ludong University, Yantai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6668-9208","authenticated-orcid":false,"given":"Weiqing","family":"Min","sequence":"additional","affiliation":[{"name":"Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6790-0239","authenticated-orcid":false,"given":"Guorui","family":"Sheng","sequence":"additional","affiliation":[{"name":"School of Computer Science and Artificial Intelligence, Ludong University, Yantai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2660-1050","authenticated-orcid":false,"given":"Tao","family":"Yao","sequence":"additional","affiliation":[{"name":"School of Computer Science and Artificial Intelligence, Ludong University, Yantai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1025-3955","authenticated-orcid":false,"given":"Lili","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Computer Science and Artificial Intelligence, Ludong University, Yantai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1596-4326","authenticated-orcid":false,"given":"Shuqiang","family":"Jiang","sequence":"additional","affiliation":[{"name":"University of Chinese Academy of Sciences, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2026,6,15]]},"reference":[{"key":"e_1_3_3_1_2_2","doi-asserted-by":"publisher","DOI":"10.1145\/2746539.2746553"},{"key":"e_1_3_3_1_3_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00423"},{"key":"e_1_3_3_1_4_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-19836-6_10"},{"key":"e_1_3_3_1_5_2","first-page":"446","volume-title":"Proc. Eur. Conf. Comput. Vis.","author":"Bossard Lukas","year":"2014","unstructured":"Lukas Bossard, Matthieu Guillaumin, and Luc Van\u00a0Gool. 2014. Food-101\u2013mining discriminative components with random forests. In Proc. Eur. Conf. Comput. Vis.Springer, Cham, 446\u2013461."},{"key":"e_1_3_3_1_6_2","unstructured":"Pindan Cao Weiqing Min Guorui Sheng Yongqiang Song Tao Yao Lili Wang and Shuqiang Jiang. 2026. FoodHash: Context-Aware Proxy Interaction and Fusion for Food Image Retrieval. ACM Trans. Multimedia Comput. Commun. Appl. (2026)."},{"key":"e_1_3_3_1_7_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.598"},{"key":"e_1_3_3_1_8_2","doi-asserted-by":"publisher","DOI":"10.1145\/2964284.2964315"},{"key":"e_1_3_3_1_9_2","doi-asserted-by":"publisher","DOI":"10.1145\/3512527.3531405"},{"key":"e_1_3_3_1_10_2","doi-asserted-by":"crossref","unstructured":"Yangdong Chen Zhaolong Zhang Yanfei Wang Yuejie Zhang Rui Feng Tao Zhang and Weiguo Fan. 2022. AE-Net: Fine-grained sketch-based image retrieval via attention-enhanced network. Pattern Recognit. 122 (2022) 108291.","DOI":"10.1016\/j.patcog.2021.108291"},{"key":"e_1_3_3_1_11_2","doi-asserted-by":"crossref","unstructured":"Zhen-Duo Chen Xin Luo Yongxin Wang Shanqing Guo and Xin-Shun Xu. 2022. Fine-grained hashing with double filtering. IEEE Trans. Image Process. 31 (2022) 1671\u20131683.","DOI":"10.1109\/TIP.2022.3145159"},{"key":"e_1_3_3_1_12_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52733.2024.01635"},{"key":"e_1_3_3_1_13_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58580-8_12"},{"key":"e_1_3_3_1_14_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2005.177"},{"key":"e_1_3_3_1_15_2","doi-asserted-by":"publisher","DOI":"10.1145\/997817.997857"},{"key":"e_1_3_3_1_16_2","doi-asserted-by":"crossref","unstructured":"Shiv\u00a0Ram Dubey. 2021. A decade survey of content based image retrieval using deep learning. IEEE Trans. Circuits Syst. Video Technol. 32 5 (2021) 2687\u20132704.","DOI":"10.1109\/TCSVT.2021.3080920"},{"key":"e_1_3_3_1_17_2","doi-asserted-by":"crossref","unstructured":"Giovanni\u00a0Maria Farinella Dario Allegra Marco Moltisanti Filippo Stanco and Sebastiano Battiato. 2016. Retrieval and classification of food images. Computers in biology and medicine 77 (2016) 23\u201339.","DOI":"10.1016\/j.compbiomed.2016.07.006"},{"key":"e_1_3_3_1_18_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.476"},{"key":"e_1_3_3_1_19_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"e_1_3_3_1_20_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.66"},{"key":"e_1_3_3_1_21_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2010.5540039"},{"key":"e_1_3_3_1_22_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.348"},{"key":"e_1_3_3_1_23_2","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v32i1.11814"},{"key":"e_1_3_3_1_24_2","doi-asserted-by":"crossref","unstructured":"Xin Jiang Hao Tang and Zechao Li. 2024. Global meets local: Dual activation hashing network for large-scale fine-grained image retrieval. IEEE Trans. Knowl. Data Eng. 36 11 (2024) 6266\u20136279.","DOI":"10.1109\/TKDE.2024.3393512"},{"key":"e_1_3_3_1_25_2","first-page":"3","volume-title":"Proc. Eur. Conf. Comput. Vis.","author":"Kawano Yoshiyuki","year":"2014","unstructured":"Yoshiyuki Kawano and Keiji Yanai. 2014. Automatic expansion of a food image dataset leveraging existing categories with domain adaptation. In Proc. Eur. Conf. Comput. Vis.Springer, Cham, 3\u201317."},{"key":"e_1_3_3_1_26_2","unstructured":"Wu-Jun Li Sheng Wang and Wang-Cheng Kang. 2015. Feature learning based deep supervised hashing with pairwise labels. arXiv:https:\/\/arXiv.org\/abs\/1511.03855 (2015)."},{"key":"e_1_3_3_1_27_2","doi-asserted-by":"crossref","unstructured":"Xue Li Jiong Yu Junlong Cheng Ziyang Li and Chen Bian. 2025. Semantic Preservation-Based Hash Code Generation for fine-grained image retrieval. Expert Sys. Appl. 271 (2025) 126668.","DOI":"10.1016\/j.eswa.2025.126668"},{"key":"e_1_3_3_1_28_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.227"},{"key":"e_1_3_3_1_29_2","doi-asserted-by":"crossref","unstructured":"David\u00a0G Lowe. 2004. Distinctive image features from scale-invariant keypoints. int. j. comput. vision 60 (2004) 91\u2013110.","DOI":"10.1023\/B:VISI.0000029664.99615.94"},{"key":"e_1_3_3_1_30_2","doi-asserted-by":"publisher","DOI":"10.1145\/3581783.3612043"},{"key":"e_1_3_3_1_31_2","doi-asserted-by":"crossref","unstructured":"Xiao Luo Haixin Wang Daqing Wu Chong Chen Minghua Deng Jianqiang Huang and Xian-Sheng Hua. 2023. A survey on deep hashing methods. ACM Trans. Knowl. Discov. Data 17 1 (2023) 1\u201350.","DOI":"10.1145\/3532624"},{"key":"e_1_3_3_1_32_2","first-page":"950","volume-title":"Int. Conf. Very Large Data Bases","author":"Lv Qin","year":"2007","unstructured":"Qin Lv, William Josephson, Zhe Wang, Moses Charikar, and Kai Li. 2007. Multi-probe LSH: efficient indexing for high-dimensional similarity search. In Int. Conf. Very Large Data Bases. VLDB Endowment, White Plains, NY, USA, 950\u2013961."},{"key":"e_1_3_3_1_33_2","doi-asserted-by":"crossref","unstructured":"Weiqing Min Shuqiang Jiang Linhu Liu Yong Rui and Ramesh Jain. 2019. A survey on food computing. ACM Comput. Surv. 52 5 (2019) 1\u201336.","DOI":"10.1145\/3329168"},{"key":"e_1_3_3_1_34_2","doi-asserted-by":"publisher","DOI":"10.1145\/3394171.3414031"},{"key":"e_1_3_3_1_35_2","doi-asserted-by":"crossref","unstructured":"Weiqing Min Zhiling Wang Yuxin Liu Mengjiang Luo Liping Kang Xiaoming Wei Xiaolin Wei and Shuqiang Jiang. 2023. Large scale visual food recognition. IEEE Trans. Pattern Anal. Mach. Intell. 45 8 (2023) 9932\u20139949.","DOI":"10.1109\/TPAMI.2023.3237871"},{"key":"e_1_3_3_1_36_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICAISC58445.2023.10200622"},{"key":"e_1_3_3_1_37_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01522"},{"key":"e_1_3_3_1_38_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-19781-9_31"},{"key":"e_1_3_3_1_39_2","doi-asserted-by":"publisher","DOI":"10.1109\/BigMM.2017.73"},{"key":"e_1_3_3_1_40_2","first-page":"1470","volume-title":"Proc. IEEE Int. Conf. Comput. Vision","year":"2003","unstructured":"Sivic and Zisserman. 2003. Video Google: A text retrieval approach to object matching in videos. In Proc. IEEE Int. Conf. Comput. Vision. IEEE, New York, NY, USA, 1470\u20131477."},{"key":"e_1_3_3_1_41_2","doi-asserted-by":"publisher","DOI":"10.1109\/MIPR54900.2022.00068"},{"key":"e_1_3_3_1_42_2","doi-asserted-by":"crossref","unstructured":"Haifeng Sun Jiaqing Xu Jingyu Wang Qi Qi Ce Ge and Jianxin Liao. 2022. DLI-Net: Dual local interaction network for fine-grained sketch-based image retrieval. IEEE Trans. Circuits Syst. Video Technol. 32 10 (2022) 7177\u20137189.","DOI":"10.1109\/TCSVT.2022.3171972"},{"key":"e_1_3_3_1_43_2","doi-asserted-by":"crossref","unstructured":"Jun Wang Wei Liu Sanjiv Kumar and Shih-Fu Chang. 2015. Learning to hash for indexing big data\u2014A survey. Proc. IEEE 104 1 (2015) 34\u201357.","DOI":"10.1109\/JPROC.2015.2487976"},{"key":"e_1_3_3_1_44_2","doi-asserted-by":"crossref","unstructured":"Jingdong Wang Ting Zhang Nicu Sebe Heng\u00a0Tao Shen et\u00a0al. 2017. A survey on learning to hash. IEEE Trans. Pattern Anal. Mach. Intell. 40 4 (2017) 769\u2013790.","DOI":"10.1109\/TPAMI.2017.2699960"},{"key":"e_1_3_3_1_45_2","doi-asserted-by":"publisher","unstructured":"Xiu-Shen Wei Yang Shen Xuhao Sun Peng Wang and Yuxin Peng. 2023. Attribute-Aware Deep Hashing With Self-Consistency for Large-Scale Fine-Grained Image Retrieval. IEEE Trans. Pattern Anal. Mach. Intell. 45 11 (2023) 13904\u201313920. 10.1109\/TPAMI.2023.3299563","DOI":"10.1109\/TPAMI.2023.3299563"},{"key":"e_1_3_3_1_46_2","unstructured":"Xiu-Shen Wei Yang Shen Xuhao Sun Han-Jia Ye and Jian Yang. 2021. A\u00a0\\(\\hat{}\\) 2-Net: Learning attribute-aware hash codes for large-scale fine-grained image retrieval. Proc. Adv. neural inf. proces. syst. 34 (2021) 5720\u20135730."},{"key":"e_1_3_3_1_47_2","doi-asserted-by":"crossref","unstructured":"Xiu-Shen Wei Yi-Zhe Song Oisin Mac\u00a0Aodha Jianxin Wu Yuxin Peng Jinhui Tang Jian Yang and Serge Belongie. 2021. Fine-grained image analysis with deep learning: A survey. IEEE Trans. Pattern Anal. Mach. Intell. 44 12 (2021) 8927\u20138948.","DOI":"10.1109\/TPAMI.2021.3126648"},{"key":"e_1_3_3_1_48_2","doi-asserted-by":"crossref","unstructured":"Xinguang Xiang Xinhao Ding Lu Jin Zechao Li Jinhui Tang and Ramesh Jain. 2024. Alleviating over-fitting in hashing-based fine-grained image retrieval: From causal feature learning to binary-injected hash learning. IEEE Trans. Multimedia 26 (2024) 10665\u201310677.","DOI":"10.1109\/TMM.2024.3410136"},{"key":"e_1_3_3_1_49_2","doi-asserted-by":"crossref","unstructured":"Han Yu Huibin Lu Min Zhao Zhuoyi Li and Guanghua Gu. 2024. Gradient aggregation based fine-grained image retrieval: A unified viewpoint for CNN and Transformer. Pattern Recognit. 149 (2024) 110248.","DOI":"10.1016\/j.patcog.2023.110248"},{"key":"e_1_3_3_1_50_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.93"},{"key":"e_1_3_3_1_51_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.557"},{"key":"e_1_3_3_1_52_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.01174"}],"event":{"name":"ICMR '26: International Conference on Multimedia Retrieval","location":"Amsterdam The Netherlands","acronym":"ICMR '26","sponsor":["SIGMM ACM Special Interest Group on Multimedia"]},"container-title":["Proceedings of the 2026 International Conference on Multimedia Retrieval"],"original-title":[],"deposited":{"date-parts":[[2026,6,15]],"date-time":"2026-06-15T15:19:26Z","timestamp":1781536766000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3805622.3810838"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,6,15]]},"references-count":51,"alternative-id":["10.1145\/3805622.3810838","10.1145\/3805622"],"URL":"https:\/\/doi.org\/10.1145\/3805622.3810838","relation":{},"subject":[],"published":{"date-parts":[[2026,6,15]]},"assertion":[{"value":"2026-06-15","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}