{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,21]],"date-time":"2026-02-21T18:35:39Z","timestamp":1771698939823,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":59,"publisher":"ACM","license":[{"start":{"date-parts":[[2023,10,26]],"date-time":"2023-10-26T00:00:00Z","timestamp":1698278400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2020YFB1406703"],"award-info":[{"award-number":["2020YFB1406703"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2023,10,26]]},"DOI":"10.1145\/3581783.3611784","type":"proceedings-article","created":{"date-parts":[[2023,10,27]],"date-time":"2023-10-27T07:27:30Z","timestamp":1698391650000},"page":"3569-3578","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":7,"title":["Semantic-based Selection, Synthesis, and Supervision for Few-shot Learning"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-7322-9942","authenticated-orcid":false,"given":"Jinda","family":"Lu","sequence":"first","affiliation":[{"name":"University of Science and Technology of China, Hefei, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4881-9344","authenticated-orcid":false,"given":"Shuo","family":"Wang","sequence":"additional","affiliation":[{"name":"University of Science and Technology of China, Hefei, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3222-7966","authenticated-orcid":false,"given":"Xinyu","family":"Zhang","sequence":"additional","affiliation":[{"name":"University of Science and Technology of China, Hefei, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0695-1566","authenticated-orcid":false,"given":"Yanbin","family":"Hao","sequence":"additional","affiliation":[{"name":"University of Science and Technology of China, Hefei, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8472-7992","authenticated-orcid":false,"given":"Xiangnan","family":"He","sequence":"additional","affiliation":[{"name":"University of Science and Technology of China, Hefei, China"}]}],"member":"320","published-online":{"date-parts":[[2023,10,27]]},"reference":[{"key":"e_1_3_2_2_1_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00891"},{"key":"e_1_3_2_2_2_1","volume-title":"International Conference on Learning Representations (ICLR), 2019. International Conference on Learning Representations.","author":"Bertinetto L","year":"2019","unstructured":"L Bertinetto, J Henriques, P Torr, and A Vedaldi. 2019. Meta-learning with differentiable closed-form solvers. In International Conference on Learning Representations (ICLR), 2019. International Conference on Learning Representations."},{"key":"e_1_3_2_2_3_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i07.6630"},{"key":"e_1_3_2_2_4_1","volume-title":"International Conference on Learning Representations.","author":"Chen Wei-Yu","year":"2019","unstructured":"Wei-Yu Chen, Yen-Cheng Liu, Zsolt Kira, Yu-Chiang Frank Wang, and Jia-Bin Huang. 2019b. A Closer Look at Few-shot Classification. In International Conference on Learning Representations."},{"key":"e_1_3_2_2_5_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00893"},{"key":"e_1_3_2_2_6_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00888"},{"key":"e_1_3_2_2_7_1","volume-title":"Advances in Neural Information Processing Systems","volume":"31","author":"Gao Hang","year":"2018","unstructured":"Hang Gao, Zheng Shou, Alireza Zareian, Hanwang Zhang, and Shih-Fu Chang. 2018. Low-shot learning via covariance-preserving adversarial augmentation networks. Advances in Neural Information Processing Systems, Vol. 31 (2018)."},{"key":"e_1_3_2_2_8_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00011"},{"key":"e_1_3_2_2_9_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2020.2984091"},{"key":"e_1_3_2_2_10_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v37i1.25150"},{"key":"e_1_3_2_2_11_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.328"},{"key":"e_1_3_2_2_12_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v36i6.20659"},{"key":"e_1_3_2_2_13_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00870"},{"key":"e_1_3_2_2_14_1","volume-title":"International Conference on Learning Representations.","author":"Diederik","unstructured":"Diederik P. Kingma and Jimmy Ba. 2015. Adam: a method for stochastic optimization. In International Conference on Learning Representations."},{"key":"e_1_3_2_2_15_1","unstructured":"Alex Krizhevsky Geoffrey Hinton et al. 2009. Learning multiple layers of features from tiny images. (2009)."},{"key":"e_1_3_2_2_16_1","first-page":"24581","article-title":"On episodes, prototypical networks, and few-shot learning","volume":"34","author":"Laenen Steinar","year":"2021","unstructured":"Steinar Laenen and Luca Bertinetto. 2021. On episodes, prototypical networks, and few-shot learning. Advances in Neural Information Processing Systems, Vol. 34 (2021), 24581--24592.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_2_17_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.01091"},{"key":"e_1_3_2_2_18_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01259"},{"key":"e_1_3_2_2_19_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00738"},{"key":"e_1_3_2_2_20_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01348"},{"key":"e_1_3_2_2_21_1","volume-title":"Proceedings of the Twenty-Ninth International Conference on International Joint Conferences on Artificial Intelligence. 2957--2963","author":"Li Wenbin","year":"2021","unstructured":"Wenbin Li, Lei Wang, Jing Huo, Yinghuan Shi, Yang Gao, and Jiebo Luo. 2021. Asymmetric distribution measure for few-shot learning. In Proceedings of the Twenty-Ninth International Conference on International Joint Conferences on Artificial Intelligence. 2957--2963."},{"key":"e_1_3_2_2_22_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i10.17047"},{"key":"e_1_3_2_2_23_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01073"},{"key":"e_1_3_2_2_24_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2021.3139918"},{"key":"e_1_3_2_2_25_1","unstructured":"Zhenguang Liu Shuang Wu Shuyuan Jin Qi Liu Shijian Lu Roger Zimmermann and Li Cheng. 2019. Towards Natural and Accurate Future Motion Prediction of Humans and Animals. In CVPR. 10004--10012."},{"key":"e_1_3_2_2_26_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00053"},{"key":"e_1_3_2_2_27_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00755"},{"key":"e_1_3_2_2_28_1","first-page":"24474","article-title":"FeLMi: few shot learning with hard mixup","volume":"35","author":"Roy Aniket","year":"2022","unstructured":"Aniket Roy, Anshul Shah, Ketul Shah, Prithviraj Dhar, Anoop Cherian, and Rama Chellappa. 2022. FeLMi: few shot learning with hard mixup. Advances in Neural Information Processing Systems, Vol. 35 (2022), 24474--24486.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_2_29_1","volume-title":"Meta-Learning with Latent Embedding Optimization. In International Conference on Learning Representations.","author":"Rusu Andrei A","year":"2019","unstructured":"Andrei A Rusu, Dushyant Rao, Jakub Sygnowski, Oriol Vinyals, Razvan Pascanu, Simon Osindero, and Raia Hadsell. 2019. Meta-Learning with Latent Embedding Optimization. In International Conference on Learning Representations."},{"key":"e_1_3_2_2_30_1","volume-title":"Delta-encoder: an effective sample synthesis method for few-shot object recognition. Advances in neural information processing systems","author":"Schwartz Eli","year":"2018","unstructured":"Eli Schwartz, Leonid Karlinsky, Joseph Shtok, Sivan Harary, Mattias Marder, Abhishek Kumar, Rogerio Feris, Raja Giryes, and Alex Bronstein. 2018. Delta-encoder: an effective sample synthesis method for few-shot object recognition. Advances in neural information processing systems, Vol. 31 (2018)."},{"key":"e_1_3_2_2_31_1","volume-title":"Prototypical networks for few-shot learning. Advances in neural information processing systems","author":"Snell Jake","year":"2017","unstructured":"Jake Snell, Kevin Swersky, and Richard Zemel. 2017. Prototypical networks for few-shot learning. Advances in neural information processing systems, Vol. 30 (2017)."},{"key":"e_1_3_2_2_32_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00049"},{"key":"e_1_3_2_2_33_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00131"},{"key":"e_1_3_2_2_34_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58568-6_16"},{"key":"e_1_3_2_2_35_1","unstructured":"Oriol Vinyals Charles Blundell Timothy Lillicrap Daan Wierstra et al. 2016. Matching networks for one shot learning. Advances in neural information processing systems Vol. 29 (2016)."},{"key":"e_1_3_2_2_36_1","unstructured":"Catherine Wah Steve Branson Peter Welinder Pietro Perona and Serge Belongie. 2011. The caltech-ucsd birds-200--2011 dataset. (2011)."},{"key":"e_1_3_2_2_37_1","doi-asserted-by":"publisher","DOI":"10.1145\/3522713"},{"key":"e_1_3_2_2_38_1","doi-asserted-by":"publisher","DOI":"10.1145\/3314577"},{"key":"e_1_3_2_2_39_1","doi-asserted-by":"publisher","DOI":"10.1145\/3240508.3240671"},{"key":"e_1_3_2_2_40_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58607-2_42"},{"key":"e_1_3_2_2_41_1","doi-asserted-by":"publisher","DOI":"10.1145\/3503161.3547837"},{"key":"e_1_3_2_2_42_1","volume-title":"2023 c. Generative recommendation: Towards next-generation recommender paradigm. arXiv preprint arXiv:2304.03516","author":"Wang Wenjie","year":"2023","unstructured":"Wenjie Wang, Xinyu Lin, Fuli Feng, Xiangnan He, and Tat-Seng Chua. 2023 c. Generative recommendation: Towards next-generation recommender paradigm. arXiv preprint arXiv:2304.03516 (2023)."},{"key":"e_1_3_2_2_43_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00760"},{"key":"e_1_3_2_2_44_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.01905"},{"key":"e_1_3_2_2_45_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00672"},{"key":"e_1_3_2_2_46_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00792"},{"key":"e_1_3_2_2_47_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00832"},{"key":"e_1_3_2_2_48_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00781"},{"key":"e_1_3_2_2_49_1","volume-title":"Advances in Neural Information Processing Systems","volume":"32","author":"Xing Chen","year":"2019","unstructured":"Chen Xing, Negar Rostamzadeh, Boris Oreshkin, and Pedro O O Pinheiro. 2019. Adaptive cross-modal few-shot learning. Advances in Neural Information Processing Systems, Vol. 32 (2019)."},{"key":"e_1_3_2_2_50_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00514"},{"key":"e_1_3_2_2_51_1","volume-title":"International Conference on Learning Representations.","author":"Xu Weijian","year":"2021","unstructured":"Weijian Xu, Yifan Xu, Huaijin Wang, and Zhuowen Tu. 2021b. Attentional constellation nets for few-shot learning. In International Conference on Learning Representations."},{"key":"e_1_3_2_2_52_1","volume-title":"Free Lunch for Few-shot Learning: Distribution Calibration. In International Conference on Learning Representations.","author":"Yang Shuo","year":"2021","unstructured":"Shuo Yang, Lu Liu, and Min Xu. 2021. Free Lunch for Few-shot Learning: Distribution Calibration. In International Conference on Learning Representations."},{"key":"e_1_3_2_2_53_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00883"},{"key":"e_1_3_2_2_54_1","volume-title":"Interventional few-shot learning. Advances in neural information processing systems","author":"Yue Zhongqi","year":"2020","unstructured":"Zhongqi Yue, Hanwang Zhang, Qianru Sun, and Xian-Sheng Hua. 2020. Interventional few-shot learning. Advances in neural information processing systems, Vol. 33 (2020), 2734--2746."},{"key":"e_1_3_2_2_55_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00375"},{"key":"e_1_3_2_2_56_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01222"},{"key":"e_1_3_2_2_57_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00930"},{"key":"e_1_3_2_2_58_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.321"},{"key":"e_1_3_2_2_59_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00829"}],"event":{"name":"MM '23: The 31st ACM International Conference on Multimedia","location":"Ottawa ON Canada","acronym":"MM '23","sponsor":["SIGMM ACM Special Interest Group on Multimedia"]},"container-title":["Proceedings of the 31st ACM International Conference on Multimedia"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3581783.3611784","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3581783.3611784","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,22]],"date-time":"2025-08-22T00:01:12Z","timestamp":1755820872000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3581783.3611784"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,10,26]]},"references-count":59,"alternative-id":["10.1145\/3581783.3611784","10.1145\/3581783"],"URL":"https:\/\/doi.org\/10.1145\/3581783.3611784","relation":{},"subject":[],"published":{"date-parts":[[2023,10,26]]},"assertion":[{"value":"2023-10-27","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}