{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,30]],"date-time":"2026-04-30T16:50:35Z","timestamp":1777567835522,"version":"3.51.4"},"publisher-location":"New York, NY, USA","reference-count":68,"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\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62171325"],"award-info":[{"award-number":["62171325"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"CAAI-Huawei MindSpore Open Fund","award":["CAAIXSJLJJ-2022-007B"],"award-info":[{"award-number":["CAAIXSJLJJ-2022-007B"]}]},{"name":"National Key R\\&D Project","award":["2021YFC3320301"],"award-info":[{"award-number":["2021YFC3320301"]}]},{"name":"Hubei Key R\\&D Project","award":["2022BAA033"],"award-info":[{"award-number":["2022BAA033"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2023,10,26]]},"DOI":"10.1145\/3581783.3611712","type":"proceedings-article","created":{"date-parts":[[2023,10,27]],"date-time":"2023-10-27T07:27:40Z","timestamp":1698391660000},"page":"3228-3239","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":22,"title":["Modal-aware Visual Prompting for Incomplete Multi-modal Brain Tumor Segmentation"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5619-0902","authenticated-orcid":false,"given":"Yansheng","family":"Qiu","sequence":"first","affiliation":[{"name":"National Engineering Research Center for Multimedia Software, School of Computer Science, Wuhan University, Wuhan, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4403-825X","authenticated-orcid":false,"given":"Ziyuan","family":"Zhao","sequence":"additional","affiliation":[{"name":"Institute for Infocomm Research (I2R), A*STAR &amp; School of Computer Science and Engineering, Nanyang Technological University, Singapore, Singapore"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6297-7138","authenticated-orcid":false,"given":"Hongdou","family":"Yao","sequence":"additional","affiliation":[{"name":"National Engineering Research Center for Multimedia Software, School of Computer Science, Wuhan University, Wuhan, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9519-093X","authenticated-orcid":false,"given":"Delin","family":"Chen","sequence":"additional","affiliation":[{"name":"National Engineering Research Center for Multimedia Software, School of Computer Science, Wuhan University, Wuhan, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3846-9157","authenticated-orcid":false,"given":"Zheng","family":"Wang","sequence":"additional","affiliation":[{"name":"National Engineering Research Center for Multimedia Software, School of Computer Science, Wuhan University, Wuhan, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2023,10,27]]},"reference":[{"key":"e_1_3_2_2_1_1","volume-title":"International Conference on Medical Imaging with Deep Learning. PMLR, 48--62","author":"Azad Reza","year":"2022","unstructured":"Reza Azad, Nika Khosravi, and Dorit Merhof. 2022. SMU-Net: Style matching U-Net for brain tumor segmentation with missing modalities. In International Conference on Medical Imaging with Deep Learning. PMLR, 48--62."},{"key":"e_1_3_2_2_2_1","unstructured":"Hyojin Bahng Ali Jahanian Swami Sankaranarayanan and Phillip Isola. 2022. Exploring Visual Prompts for Adapting Large-Scale Models. arxiv: 2203.17274 [cs.CV]"},{"key":"e_1_3_2_2_3_1","doi-asserted-by":"publisher","DOI":"10.1111\/bpa.13060"},{"key":"e_1_3_2_2_4_1","first-page":"25005","article-title":"Visual prompting via image inpainting","volume":"35","author":"Bar Amir","year":"2022","unstructured":"Amir Bar, Yossi Gandelsman, Trevor Darrell, Amir Globerson, and Alexei Efros. 2022. Visual prompting via image inpainting. Advances in Neural Information Processing Systems, Vol. 35 (2022), 25005--25017.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_2_5_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2022.acl-short.1"},{"key":"e_1_3_2_2_6_1","unstructured":"Tom Brown Benjamin Mann Nick Ryder Melanie Subbiah Jared D Kaplan Prafulla Dhariwal Arvind Neelakantan Pranav Shyam Girish Sastry Amanda Askell et al. 2020. Language models are few-shot learners. Advances in neural information processing systems Vol. 33 (2020) 1877--1901."},{"key":"e_1_3_2_2_7_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-32248-9_50"},{"key":"e_1_3_2_2_8_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2021.3119385"},{"key":"e_1_3_2_2_9_1","volume-title":"Advances in Neural Information Processing Systems","volume":"35","author":"Chen Shoufa","year":"2022","unstructured":"Shoufa Chen, Chongjian GE, Zhan Tong, Jiangliu Wang, Yibing Song, Jue Wang, and Ping Luo. 2022. AdaptFormer: Adapting Vision Transformers for Scalable Visual Recognition. In Advances in Neural Information Processing Systems, Vol. 35. Curran Associates, Inc., 16664--16678."},{"key":"e_1_3_2_2_10_1","doi-asserted-by":"publisher","DOI":"10.2307\/1932409"},{"key":"e_1_3_2_2_11_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i2.16212"},{"key":"e_1_3_2_2_12_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00394"},{"key":"e_1_3_2_2_13_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-32245-8_9"},{"key":"e_1_3_2_2_14_1","volume-title":"Adv. Neural Inf. Process. Syst.","volume":"27","author":"Ian","year":"2014","unstructured":"Ian Goodfellow et al. 2014. Generative adversarial nets. Adv. Neural Inf. Process. Syst., Vol. 27 (2014)."},{"key":"e_1_3_2_2_15_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46723-8_54"},{"key":"e_1_3_2_2_16_1","volume-title":"Gaussian error linear units (gelus). arXiv preprint arXiv:1606.08415","author":"Hendrycks Dan","year":"2016","unstructured":"Dan Hendrycks and Kevin Gimpel. 2016. Gaussian error linear units (gelus). arXiv preprint arXiv:1606.08415 (2016)."},{"key":"e_1_3_2_2_17_1","volume-title":"International Conference on Machine Learning. PMLR, 2790--2799","author":"Houlsby Neil","year":"2019","unstructured":"Neil Houlsby, Andrei Giurgiu, Stanislaw Jastrzebski, Bruna Morrone, Quentin De Laroussilhe, Andrea Gesmundo, Mona Attariyan, and Sylvain Gelly. 2019. Parameter-efficient transfer learning for NLP. In International Conference on Machine Learning. PMLR, 2790--2799."},{"key":"e_1_3_2_2_18_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-59710-8_75"},{"key":"e_1_3_2_2_19_1","volume-title":"Medical Image Computing and Computer Assisted Intervention","author":"Huang Ziqi","unstructured":"Ziqi Huang, Li Lin, Pujin Cheng, Kai Pan, and Xiaoying Tang. 2022. DS 3-Net: Difficulty-Perceived Common-to-T1ce Semi-supervised Multimodal MRI Synthesis Network. In Medical Image Computing and Computer Assisted Intervention. Springer, 571--581."},{"key":"e_1_3_2_2_20_1","volume-title":"Computer Vision - ECCV 2022 - 17th European Conference","author":"Jia Menglin","unstructured":"Menglin Jia, Luming Tang, Bor-Chun Chen, Claire Cardie, Serge Belongie, Bharath Hariharan, and Ser-Nam Lim. 2022a. Visual prompt tuning. In Computer Vision - ECCV 2022 - 17th European Conference, Vol. '13693'. Springer, 'Israel', '709--727'."},{"key":"e_1_3_2_2_21_1","volume-title":"'709--727'.","author":"Jia Menglin","year":"2022","unstructured":"Menglin Jia, Luming Tang, Bor-Chun Chen, Claire Cardie, Serge Belongie, Bharath Hariharan, and Ser-Nam Lim. 2022b. Visual prompt tuning. In ECCV. 'Springer', '709--727'."},{"key":"e_1_3_2_2_22_1","volume-title":"MaPLe: Multi-modal Prompt Learning. ArXiv:2210.03117","author":"Khattak Muhammad Uzair","year":"2022","unstructured":"Muhammad Uzair Khattak, Hanoona Rasheed, Muhammad Maaz, Salman Khan, and Fahad Shahbaz Khan. 2022. MaPLe: Multi-modal Prompt Learning. ArXiv:2210.03117, Vol. 'abs\/2210.03117' (2022)."},{"key":"e_1_3_2_2_23_1","doi-asserted-by":"crossref","unstructured":"Sein Kim Namkyeong Lee Junseok Lee Dongmin Hyun and Chanyoung Park. 2022. Heterogeneous Graph Learning for Multi-modal Medical Data Analysis. In AAAI.","DOI":"10.1609\/aaai.v37i4.25643"},{"key":"e_1_3_2_2_24_1","volume-title":"Proc. Int. Conf. Learn. Represent.","author":"Kingma Diederik P","year":"2015","unstructured":"Diederik P Kingma and Jimmy Ba. 2015. Adam: A Method for Stochastic Optimization. In Proc. Int. Conf. Learn. Represent."},{"key":"e_1_3_2_2_25_1","volume-title":"arXiv:2304.02643","author":"Kirillov Alexander","year":"2023","unstructured":"Alexander Kirillov, Eric Mintun, Nikhila Ravi, Hanzi Mao, Chloe Rolland, Laura Gustafson, Tete Xiao, Spencer Whitehead, Alexander C. Berg, Wan-Yen Lo, Piotr Doll\u00e1r, and Ross Girshick. 2023. Segment Anything. arXiv:2304.02643 (2023)."},{"key":"e_1_3_2_2_26_1","doi-asserted-by":"publisher","DOI":"10.1038\/s42256-019-0137-x"},{"key":"e_1_3_2_2_27_1","volume-title":"3D UX-Net: A Large Kernel Volumetric ConvNet Modernizing Hierarchical Transformer for Medical Image Segmentation. arXiv preprint arXiv:2209.15076","author":"Lee Ho Hin","year":"2022","unstructured":"Ho Hin Lee, Shunxing Bao, Yuankai Huo, and Bennett A Landman. 2022. 3D UX-Net: A Large Kernel Volumetric ConvNet Modernizing Hierarchical Transformer for Medical Image Segmentation. arXiv preprint arXiv:2209.15076, Vol. 'abs\/2209.15076' (2022)."},{"key":"e_1_3_2_2_28_1","volume-title":"Multimodal Prompting with Missing Modalities for Visual Recognition. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR). 'IEEE'.","author":"Lee Yi-Lun","year":"2023","unstructured":"Yi-Lun Lee, Yi-Hsuan Tsai, Wei-Chen Chiu, and Chen-Yu Lee. 2023. Multimodal Prompting with Missing Modalities for Visual Recognition. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR). 'IEEE'."},{"key":"e_1_3_2_2_29_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.emnlp-main.243"},{"key":"e_1_3_2_2_30_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-10443-0_39"},{"key":"e_1_3_2_2_31_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.acl-long.353"},{"key":"e_1_3_2_2_32_1","volume-title":"Modular and Parameter-Efficient Multimodal Fusion with Prompting. In Findings of the Association for Computational Linguistics: ACL","author":"Liang Sheng","year":"2022","unstructured":"Sheng Liang, Mengjie Zhao, and Hinrich Sch\u00fctze. 2022. Modular and Parameter-Efficient Multimodal Fusion with Prompting. In Findings of the Association for Computational Linguistics: ACL 2022. 'Association for Computational Linguistics', '2976--2985'."},{"key":"e_1_3_2_2_33_1","volume-title":"Huahong Zhang, and Ipek Oguz.","author":"Liu Han","year":"2022","unstructured":"Han Liu, Yubo Fan, Hao Li, Jiacheng Wang, Dewei Hu, Can Cui, Ho Hin Lee, Huahong Zhang, and Ipek Oguz. 2022. ModDrop: A Dynamic Filter Network with Intra-subject Co-training for Multiple Sclerosis Lesion Segmentation with Missing Modalities. In Medical Image Computing and Computer Assisted Intervention. Springer, 444--453."},{"key":"e_1_3_2_2_34_1","doi-asserted-by":"crossref","unstructured":"Pengfei Liu Weizhe Yuan Jinlan Fu Zhengbao Jiang Hiroaki Hayashi and Graham Neubig. 2023 b. Pre-train prompt and predict: A systematic survey of prompting methods in natural language processing. ACM Comput. Surv. Vol. '55' '9' (2023) '195:1--195:35'.","DOI":"10.1145\/3560815"},{"key":"e_1_3_2_2_35_1","unstructured":"Weihuang Liu Xi Shen Chi-Man Pun and Xiaodong Cun. 2023 a. Explicit Visual Prompting for Low-Level Structure Segmentations. In CPVR. 'IEEE'."},{"key":"e_1_3_2_2_36_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2020.101953"},{"key":"e_1_3_2_2_37_1","volume-title":"'18156--18165'.","author":"Ma Mengmeng","year":"2022","unstructured":"Mengmeng Ma, Jian Ren, Long Zhao, Davide Testuggine, and Xi Peng. 2022. Are Multimodal Transformers Robust to Missing Modality?. In CVPR. 'IEEE', '18156--18165'."},{"key":"e_1_3_2_2_38_1","volume-title":"'2302--2310'.","author":"Ma Mengmeng","year":"2021","unstructured":"Mengmeng Ma, Jian Ren, Long Zhao, Sergey Tulyakov, Cathy Wu, and Xi Peng. 2021. SMIL: Multimodal learning with severely missing modality. In AAAI. 'AAAI Press', '2302--2310'."},{"key":"e_1_3_2_2_39_1","unstructured":"Bjoern H Menze Andras Jakab Stefan Bauer Jayashree Kalpathy-Cramer Keyvan Farahani Justin Kirby Yuliya Burren Nicole Porz Johannes Slotboom Roland Wiest et al. 2014. The multimodal brain tumor image segmentation benchmark (BRATS). IEEE transactions on medical imaging Vol. 34 10 (2014) 1993--2024."},{"key":"e_1_3_2_2_40_1","unstructured":"OpenAI. 2023. GPT-4 Technical Report. ArXiv Vol. abs\/2303.08774 (2023)."},{"key":"e_1_3_2_2_41_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-16443-9_16"},{"key":"e_1_3_2_2_42_1","first-page":"5416","article-title":"Blending anti-aliasing into vision transformer","volume":"34","author":"Qian Shengju","year":"2021","unstructured":"Shengju Qian, Hao Shao, Yi Zhu, Mu Li, and Jiaya Jia. 2021. Blending anti-aliasing into vision transformer. Advances in Neural Information Processing Systems, Vol. 34 (2021), 5416--5429.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_2_43_1","volume-title":"What Makes for Good Tokenizers in Vision Transformer? IEEE Transactions on Pattern Analysis and Machine Intelligence","author":"Qian Shengju","year":"2022","unstructured":"Shengju Qian, Yi Zhu, Wenbo Li, Mu Li, and Jiaya Jia. 2022. What Makes for Good Tokenizers in Vision Transformer? IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 'abs\/2212.11115' (2022)."},{"key":"e_1_3_2_2_44_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.01949"},{"key":"e_1_3_2_2_45_1","volume-title":"U-net: Convolutional networks for biomedical image segmentation. In Medical Image Computing and Computer-Assisted Intervention-MICCAI 2015: 18th International Conference","author":"Ronneberger Olaf","year":"2015","unstructured":"Olaf Ronneberger, Philipp Fischer, and Thomas Brox. 2015. U-net: Convolutional networks for biomedical image segmentation. In Medical Image Computing and Computer-Assisted Intervention-MICCAI 2015: 18th International Conference, Munich, Germany, October 5-9, 2015, Proceedings, Part III 19. Springer, 234--241."},{"key":"e_1_3_2_2_46_1","volume-title":"MedNeXt: Transformer-driven Scaling of ConvNets for Medical Image Segmentation. arXiv preprint arXiv:2303.09975","author":"Roy Saikat","year":"2023","unstructured":"Saikat Roy, Gregor Koehler, Constantin Ulrich, Michael Baumgartner, Jens Petersen, Fabian Isensee, Paul F Jaeger, and Klaus Maier-Hein. 2023. MedNeXt: Transformer-driven Scaling of ConvNets for Medical Image Segmentation. arXiv preprint arXiv:2303.09975, Vol. 'abs\/2303.09975' (2023)."},{"key":"e_1_3_2_2_47_1","volume-title":"Thomas Hogue Sanford, Sherif Mehralivand, Peter L Choyke, et al.","author":"Shen Liyue","year":"2020","unstructured":"Liyue Shen, Wentao Zhu, Xiaosong Wang, Lei Xing, John M Pauly, Baris Turkbey, Stephanie Anne Harmon, Thomas Hogue Sanford, Sherif Mehralivand, Peter L Choyke, et al. 2020. Multi-domain image completion for random missing input data. IEEE transactions on medical imaging, Vol. 40, 4 (2020), 1113--1122."},{"key":"e_1_3_2_2_48_1","volume-title":"Ong","author":"Tan Zhi-Xuan","year":"2020","unstructured":"Zhi-Xuan Tan, Harold Soh, and Desmond C. Ong. 2020. Factorized Inference in Deep Markov Models for Incomplete Multimodal Time Series. In The Thirty-Fourth AAAI Conference on Artificial Intelligence, AAAI 2020, The Thirty-Second Innovative Applications of Artificial Intelligence Conference, IAAI 2020, The Tenth AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2020, New York, NY, USA, February 7-12, 2020. AAAI Press, 10334--10341."},{"key":"e_1_3_2_2_49_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.02007"},{"key":"e_1_3_2_2_50_1","volume-title":"'200--212'.","author":"Tsimpoukelli Maria","year":"2021","unstructured":"Maria Tsimpoukelli, Jacob L Menick, Serkan Cabi, SM Eslami, Oriol Vinyals, and Felix Hill. 2021. Multimodal few-shot learning with frozen language models. NeurIPS (2021), '200--212'."},{"key":"e_1_3_2_2_51_1","unstructured":"Melissa Vibberts. 2021. Incomplete Scans and Lost Revenue In MRI. https:\/\/blog.beekley.com\/incomplete-scans-and-lost-revenue-in-mri."},{"key":"e_1_3_2_2_52_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00918"},{"key":"e_1_3_2_2_53_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-87234-2_39"},{"key":"e_1_3_2_2_54_1","volume-title":"'631--648'.","author":"Wang Zifeng","year":"2022","unstructured":"Zifeng Wang, Zizhao Zhang, Sayna Ebrahimi, Ruoxi Sun, Han Zhang, Chen-Yu Lee, Xiaoqi Ren, Guolong Su, Vincent Perot, Jennifer Dy, et al. 2022a. DualPrompt: Complementary Prompting for Rehearsal-free Continual Learning. In ECCV. 'Springer', '631--648'."},{"key":"e_1_3_2_2_55_1","volume-title":"'139--149'.","author":"Wang Zifeng","year":"2022","unstructured":"Zifeng Wang, Zizhao Zhang, Chen-Yu Lee, Han Zhang, Ruoxi Sun, Xiaoqi Ren, Guolong Su, Vincent Perot, Jennifer Dy, and Tomas Pfister. 2022b. Learning to prompt for continual learning. In CVPR. 'IEEE', '139--149'."},{"key":"e_1_3_2_2_56_1","volume-title":"'3492--3500'.","author":"Yang Jinyu","year":"2022","unstructured":"Jinyu Yang, Zhe Li, Feng Zheng, Ales Leonardis, and Jingkuan Song. 2022. Prompting for Multi-Modal Tracking. In ACM MM. 'ACM', '3492--3500'."},{"key":"e_1_3_2_2_57_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2019.2895894"},{"key":"e_1_3_2_2_58_1","volume-title":"'1545--1554'.","author":"Zeng Jiandian","year":"2022","unstructured":"Jiandian Zeng, Tianyi Liu, and Jiantao Zhou. 2022. Tag-assisted Multimodal Sentiment Analysis under Uncertain Missing Modalities. In SIGIR. ACM, 'Madrid, Spain', '1545--1554'."},{"key":"e_1_3_2_2_59_1","volume-title":"Huazhu Fu, and Qinghua Hu.","author":"Zhang Changqing","year":"2020","unstructured":"Changqing Zhang, Yajie Cui, Zongbo Han, Joey Tianyi Zhou, Huazhu Fu, and Qinghua Hu. 2020. Deep partial multi-view learning. IEEE transactions on pattern analysis and machine intelligence, Vol. '44', '5' (2020), '2402--2415'."},{"key":"e_1_3_2_2_60_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-16443-9_11"},{"key":"e_1_3_2_2_61_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00874"},{"key":"e_1_3_2_2_62_1","doi-asserted-by":"crossref","unstructured":"Jinming Zhao Ruichen Li and Qin Jin. 2021. Missing modality imagination network for emotion recognition with uncertain missing modalities. In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (ACL-IJCNLP). 'Association for Computational Linguistics' 2608--2618' pages.","DOI":"10.18653\/v1\/2021.acl-long.203"},{"key":"e_1_3_2_2_63_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP43922.2022.9746910"},{"key":"e_1_3_2_2_64_1","volume-title":"International Conference on Medical Image Computing and Computer-Assisted Intervention","author":"Zhao Zechen","unstructured":"Zechen Zhao, Heran Yang, and Jian Sun. 2022b. Modality-Adaptive Feature Interaction for Brain Tumor Segmentation with Missing Modalities. In International Conference on Medical Image Computing and Computer-Assisted Intervention. Springer, 183--192."},{"key":"e_1_3_2_2_65_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2022.3214766"},{"key":"e_1_3_2_2_66_1","volume-title":"Meta-hallucinator: Towards Few-Shot Cross-Modality Cardiac Image Segmentation. In Medical Image Computing and Computer Assisted Intervention - MICCAI","author":"Zhao Ziyuan","year":"2022","unstructured":"Ziyuan Zhao, Fangcheng Zhou, Zeng Zeng, Cuntai Guan, and S. Kevin Zhou. 2022c. Meta-hallucinator: Towards Few-Shot Cross-Modality Cardiac Image Segmentation. In Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, Linwei Wang, Qi Dou, P. Thomas Fletcher, Stefanie Speidel, and Shuo Li (Eds.). Springer Nature Switzerland, Cham, 128--139."},{"key":"e_1_3_2_2_67_1","volume-title":"nnFormer: Interleaved Transformer for Volumetric Segmentation. CoRR","author":"Zhou Hong-Yu","year":"2021","unstructured":"Hong-Yu Zhou, Jiansen Guo, Yinghao Zhang, Lequan Yu, Liansheng Wang, and Yizhou Yu. 2021. nnFormer: Interleaved Transformer for Volumetric Segmentation. CoRR, Vol. abs\/2109.03201 (2021). https:\/\/arxiv.org\/abs\/2109.03201"},{"key":"e_1_3_2_2_68_1","volume-title":"Chen Change Loy, and Ziwei Liu","author":"Zhou Kaiyang","year":"2022","unstructured":"Kaiyang Zhou, Jingkang Yang, Chen Change Loy, and Ziwei Liu. 2022. Learning to prompt for vision-language models. Int. J. Comput. Vis., Vol. '130', '9' (2022), '2337--2348'."}],"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\/3581783.3611712","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3581783.3611712","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,22]],"date-time":"2025-08-22T00:05:12Z","timestamp":1755821112000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3581783.3611712"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,10,26]]},"references-count":68,"alternative-id":["10.1145\/3581783.3611712","10.1145\/3581783"],"URL":"https:\/\/doi.org\/10.1145\/3581783.3611712","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"}}]}}