{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,20]],"date-time":"2026-05-20T05:23:29Z","timestamp":1779254609469,"version":"3.51.4"},"publisher-location":"New York, NY, USA","reference-count":37,"publisher":"ACM","funder":[{"name":"Natural Science Basic Research Plan in Shaanxi Province of China under Grant","award":["2024JC-YBQN- 0661"],"award-info":[{"award-number":["2024JC-YBQN- 0661"]}]},{"name":"Nanning Scientific Research and Technological Development Project","award":["20231042"],"award-info":[{"award-number":["20231042"]}]},{"name":"Projects of the Industrial Research Plan of Guangxi Institute of Industrial Technology","award":["CYY-HT2023-JSJJ-0021"],"award-info":[{"award-number":["CYY-HT2023-JSJJ-0021"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2025,10,27]]},"DOI":"10.1145\/3746027.3755641","type":"proceedings-article","created":{"date-parts":[[2025,10,25]],"date-time":"2025-10-25T07:26:55Z","timestamp":1761377215000},"page":"4866-4874","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["SP-Mamba: Spatial-Perception State Space Model for Unsupervised Medical Anomaly Detection"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0003-7767-4265","authenticated-orcid":false,"given":"Rui","family":"Pan","sequence":"first","affiliation":[{"name":"Faculty of Integrated Circuit, Xidian University, Chang'an Qu, Xi'an Shi, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8825-6064","authenticated-orcid":false,"given":"Ruiying","family":"Lu","sequence":"additional","affiliation":[{"name":"School of Cyber Engineering, Xidian University, Chang'an Qu, Xi'an Shi, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2025,10,27]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"BMAD: Benchmarks for Medical Anomaly Detection","author":"Bao Jinan","year":"2024","unstructured":"Jinan Bao, Hanshi Sun, Hanqiu Deng, Yinsheng He, Zhaoxiang Zhang, and Xingyu Li. 2024. BMAD: Benchmarks for Medical Anomaly Detection. http:\/\/arxiv.org\/abs\/2306.11876 arXiv:2306.11876 [eess]."},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-16437-8_56"},{"key":"e_1_3_2_1_3_1","unstructured":"Yuanhong Chen Yu Tian Guansong Pang and Gustavo Carneiro. 2022. Deep One-Class Classification via Interpolated Gaussian Descriptor. arXiv:2101.10043 [cs.CV] https:\/\/arxiv.org\/abs\/2101.10043"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"crossref","unstructured":"Thomas Defard Aleksandr Setkov Angelique Loesch and Romaric Audigier. 2020. PaDiM: a Patch Distribution Modeling Framework for Anomaly Detection and Localization. arXiv:2011.08785 [cs.CV] https:\/\/arxiv.org\/abs\/2011.08785","DOI":"10.1007\/978-3-030-68799-1_35"},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00951"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1145\/3464423"},{"key":"e_1_3_2_1_7_1","volume-title":"Mamba: Linear-time sequence modeling with selective state spaces. arXiv preprint arXiv:2312.00752","author":"Gu Albert","year":"2023","unstructured":"Albert Gu and Tri Dao. 2023. Mamba: Linear-time sequence modeling with selective state spaces. arXiv preprint arXiv:2312.00752 (2023)."},{"key":"e_1_3_2_1_8_1","volume-title":"Mamba: Linear-Time Sequence Modeling with Selective State Spaces. arXiv:2312.00752 [cs.LG] https:\/\/arxiv.org\/abs\/2312.00752","author":"Gu Albert","year":"2024","unstructured":"Albert Gu and Tri Dao. 2024. Mamba: Linear-Time Sequence Modeling with Selective State Spaces. arXiv:2312.00752 [cs.LG] https:\/\/arxiv.org\/abs\/2312.00752"},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","unstructured":"Hang Guo Yong Guo Yaohua Zha Yulun Zhang Wenbo Li Tao Dai Shu-Tao Xia and Yawei Li. 2025. MambaIRv2: Attentive State Space Restoration. doi:10.48550\/arXiv.2411.15269 arXiv:2411.15269 [eess].","DOI":"10.48550\/arXiv.2411.15269"},{"key":"e_1_3_2_1_10_1","volume-title":"Zongwei Zhou, Michael B Gotway, and Jianming Liang.","author":"Haghighi Fatemeh","year":"2021","unstructured":"Fatemeh Haghighi, Mohammad Reza Hosseinzadeh Taher, Zongwei Zhou, Michael B Gotway, and Jianming Liang. 2021. Transferable visual words: Exploiting the semantics of anatomical patterns for self-supervised learning. IEEE transactions on medical imaging, Vol. 40, 10 (2021), 2857-2868."},{"key":"e_1_3_2_1_11_1","unstructured":"Haoyang He Yuhu Bai Jiangning Zhang Qingdong He Hongxu Chen Zhenye Gan Chengjie Wang Xiangtai Li Guanzhong Tian and Lei Xie. 2024. MambaAD: Exploring State Space Models for Multi-class Unsupervised Anomaly Detection. http:\/\/arxiv.org\/abs\/2404.06564 arXiv:2404.06564 [cs]."},{"key":"e_1_3_2_1_12_1","unstructured":"Haoyang He Jiangning Zhang Hongxu Chen Xuhai Chen Zhishan Li Xu Chen Yabiao Wang Chengjie Wang and Lei Xie. 2023. DiAD: A Diffusion-based Framework for Multi-class Anomaly Detection. arXiv:2312.06607 [cs.CV] https:\/\/arxiv.org\/abs\/2312.06607"},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52733.2024.01081"},{"key":"e_1_3_2_1_14_1","volume-title":"Ng","author":"Irvin Jeremy","year":"2019","unstructured":"Jeremy Irvin, Pranav Rajpurkar, Michael Ko, Yifan Yu, Silviana Ciurea-Ilcus, Chris Chute, Henrik Marklund, Behzad Haghgoo, Robyn Ball, Katie Shpanskaya, Jayne Seekins, David A. Mong, Safwan S. Halabi, Jesse K. Sandberg, Ricky Jones, David B. Larson, Curtis P. Langlotz, Bhavik N. Patel, Matthew P. Lungren, and Andrew Y. Ng. 2019. CheXpert: A Large Chest Radiograph Dataset with Uncertainty Labels and Expert Comparison. arXiv:1901.07031 [cs.CV] https:\/\/arxiv.org\/abs\/1901.07031"},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cell.2018.02.010"},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00954"},{"key":"e_1_3_2_1_17_1","volume-title":"Vmamba: Visual state space model. Advances in neural information processing systems","author":"Liu Yue","year":"2024","unstructured":"Yue Liu, Yunjie Tian, Yuzhong Zhao, Hongtian Yu, Lingxi Xie, Yaowei Wang, Qixiang Ye, Jianbin Jiao, and Yunfan Liu. 2024b. Vmamba: Visual state space model. Advances in neural information processing systems, Vol. 37 (2024), 103031-103063."},{"key":"e_1_3_2_1_18_1","unstructured":"Yue Liu Yunjie Tian Yuzhong Zhao Hongtian Yu Lingxi Xie Yaowei Wang Qixiang Ye and Yunfan Liu. 2024a. VMamba: Visual State Space Model. http:\/\/arxiv.org\/abs\/2401.10166 arXiv:2401.10166 [cs]."},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.01954"},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2024.3381435"},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"crossref","unstructured":"Sergio Naval Marimont and Giacomo Tarroni. 2021. Implicit field learning for unsupervised anomaly detection in medical images. arXiv:2106.05214 [eess.IV] https:\/\/arxiv.org\/abs\/2106.05214","DOI":"10.1007\/978-3-030-87196-3_18"},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00283"},{"key":"e_1_3_2_1_23_1","volume-title":"Vm-unet: Vision mamba unet for medical image segmentation. arXiv preprint arXiv:2402.02491","author":"Ruan Jiacheng","year":"2024","unstructured":"Jiacheng Ruan, Jincheng Li, and Suncheng Xiang. 2024. Vm-unet: Vision mamba unet for medical image segmentation. arXiv preprint arXiv:2402.02491 (2024)."},{"key":"e_1_3_2_1_24_1","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 14902-14912","author":"Salehi Mohammadreza","unstructured":"Mohammadreza Salehi, Niousha Sadjadi, Soroosh Baselizadeh, Mohammad H. Rohban, and Hamid R. Rabiee. 2021. Multiresolution Knowledge Distillation for Anomaly Detection. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 14902-14912."},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2019.01.010"},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"crossref","unstructured":"Thomas Schlegl Philipp Seeb\u00f6ck Sebastian M. Waldstein Ursula Schmidt-Erfurth and Georg Langs. 2017. Unsupervised Anomaly Detection with Generative Adversarial Networks to Guide Marker Discovery. arXiv:1703.05921 [cs.CV] https:\/\/arxiv.org\/abs\/1703.05921","DOI":"10.1007\/978-3-319-59050-9_12"},{"key":"e_1_3_2_1_27_1","unstructured":"Yuan Shi Bin Xia Xiaoyu Jin Xing Wang Tianyu Zhao Xin Xia Xuefeng Xiao and Wenming Yang. 2024. VmambaIR: Visual State Space Model for Image Restoration. arXiv:2403.11423 [cs.CV] https:\/\/arxiv.org\/abs\/2403.11423"},{"key":"e_1_3_2_1_28_1","volume-title":"Vmambair: Visual state space model for image restoration","author":"Shi Yuan","year":"2025","unstructured":"Yuan Shi, Bin Xia, Xiaoyu Jin, Xing Wang, Tianyu Zhao, Xin Xia, Xuefeng Xiao, and Wenming Yang. 2025. Vmambair: Visual state space model for image restoration. IEEE Transactions on Circuits and Systems for Video Technology (2025)."},{"key":"e_1_3_2_1_29_1","volume-title":"Mamba-unet: Unet-like pure visual mamba for medical image segmentation. arXiv preprint arXiv:2402.05079","author":"Wang Ziyang","year":"2024","unstructured":"Ziyang Wang, Jian-Qing Zheng, Yichi Zhang, Ge Cui, and Lei Li. 2024a. Mamba-unet: Unet-like pure visual mamba for medical image segmentation. arXiv preprint arXiv:2402.05079 (2024)."},{"key":"e_1_3_2_1_30_1","doi-asserted-by":"publisher","unstructured":"Ziyang Wang Jian-Qing Zheng Yichi Zhang Ge Cui and Lei Li. 2024b. Mamba-UNet: UNet-Like Pure Visual Mamba for Medical Image Segmentation. doi:10.48550\/arXiv.2402.05079 arXiv:2402.05079 [eess].","DOI":"10.48550\/arXiv.2402.05079"},{"key":"e_1_3_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2024.3382009"},{"key":"e_1_3_2_1_32_1","volume-title":"SQUID: Deep Feature In-Painting for Unsupervised Anomaly Detection","author":"Xiang Tiange","year":"2023","unstructured":"Tiange Xiang, Yixiao Zhang, Yongyi Lu, Alan L. Yuille, Chaoyi Zhang, Weidong Cai, and Zongwei Zhou. 2023. SQUID: Deep Feature In-Painting for Unsupervised Anomaly Detection. http:\/\/arxiv.org\/abs\/2111.13495 arXiv:2111.13495 [cs]."},{"key":"e_1_3_2_1_33_1","doi-asserted-by":"crossref","unstructured":"Jianpeng Zhang Yutong Xie Guansong Pang Zhibin Liao Johan Verjans Wenxing Li Zongji Sun Jian He Yi Li Chunhua Shen et al. 2020. Viral pneumonia screening on chest X-rays using confidence-aware anomaly detection. IEEE transactions on medical imaging Vol. 40 3 (2020) 879-890.","DOI":"10.1109\/TMI.2020.3040950"},{"key":"e_1_3_2_1_34_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.00381"},{"key":"e_1_3_2_1_35_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2021.3093883"},{"key":"e_1_3_2_1_36_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2021.3093883"},{"key":"e_1_3_2_1_37_1","volume-title":"Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Model","author":"Zhu Lianghui","year":"2024","unstructured":"Lianghui Zhu, Bencheng Liao, Qian Zhang, Xinlong Wang, Wenyu Liu, and Xinggang Wang. 2024. Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Model. http:\/\/arxiv.org\/abs\/2401.09417 arXiv:2401.09417 [cs]."}],"event":{"name":"MM '25: The 33rd ACM International Conference on Multimedia","location":"Dublin Ireland","acronym":"MM '25","sponsor":["SIGMM ACM Special Interest Group on Multimedia"]},"container-title":["Proceedings of the 33rd ACM International Conference on Multimedia"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3746027.3755641","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,12,10]],"date-time":"2025-12-10T05:05:36Z","timestamp":1765343136000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3746027.3755641"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,10,27]]},"references-count":37,"alternative-id":["10.1145\/3746027.3755641","10.1145\/3746027"],"URL":"https:\/\/doi.org\/10.1145\/3746027.3755641","relation":{},"subject":[],"published":{"date-parts":[[2025,10,27]]},"assertion":[{"value":"2025-10-27","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}