{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,15]],"date-time":"2026-06-15T15:54:57Z","timestamp":1781538897196,"version":"3.54.5"},"publisher-location":"New York, NY, USA","reference-count":34,"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\/3805622.3810581","type":"proceedings-article","created":{"date-parts":[[2026,6,15]],"date-time":"2026-06-15T14:42:57Z","timestamp":1781534577000},"page":"2543-2551","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["CB-CV: A Cluster-Based Cross-Validation Benchmark for Multimodal Video Out-of-Distribution Detection"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0006-2775-1914","authenticated-orcid":false,"given":"Ji","family":"Zhang","sequence":"first","affiliation":[{"name":"Department of Statistics and Operations Research, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7987-3714","authenticated-orcid":false,"given":"Xiao","family":"Luo","sequence":"additional","affiliation":[{"name":"Department of Statistics, University of Wisconsin\u2013Madison, Madison, WI, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-9535-6287","authenticated-orcid":false,"given":"Hang","family":"Zhou","sequence":"additional","affiliation":[{"name":"Department of Statistics and Operations Research, The University of North Carolina at Chapel Hill, Chapel Hill, NC, USA and School of Data Science and Society, The University of North Carolina at Chapel Hill, Chapel Hill, NC, USA"}],"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\/3746027.3762073"},{"key":"e_1_3_3_1_3_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.502"},{"key":"e_1_3_3_1_4_2","first-page":"720","volume-title":"Proceedings of the European Conference on Computer Vision (ECCV)","author":"Damen Dima","year":"2018","unstructured":"Dima Damen, Hazel Doughty, Giovanni\u00a0Maria Farinella, Sanja Fidler, Antonino Furnari, Evangelos Kazakos, Davide Moltisanti, Jonathan Munro, Toby Perrett, Will Price, et\u00a0al. 2018. Scaling Egocentric Vision: The EPIC-KITCHENS Dataset. In Proceedings of the European Conference on Computer Vision (ECCV). 720\u2013736."},{"key":"e_1_3_3_1_5_2","volume-title":"Proceedings of the International Conference on Learning Representations (ICLR)","author":"Djurisic Andrija","year":"2023","unstructured":"Andrija Djurisic, Nebojsa Bozanic, Arjun Ashok, and Rosanne Liu. 2023. Extremely Simple Activation Shaping for Out-of-Distribution Detection. In Proceedings of the International Conference on Learning Representations (ICLR)."},{"key":"e_1_3_3_1_6_2","first-page":"129250","volume-title":"Advances in Neural Information Processing Systems (NeurIPS)","author":"Dong Hao","year":"2024","unstructured":"Hao Dong, Yue Zhao, Eleni Chatzi, and Olga Fink. 2024. MultiOOD: Scaling Out-of-Distribution Detection for Multiple Modalities. In Advances in Neural Information Processing Systems (NeurIPS) , Vol.\u00a037. 129250\u2013129278."},{"key":"e_1_3_3_1_7_2","volume-title":"Proceedings of the International Conference on Learning Representations (ICLR)","author":"Du Xuefeng","year":"2022","unstructured":"Xuefeng Du, Zhaoning Wang, Mu Cai, and Yixuan Li. 2022. VOS: Learning What You Don\u2019t Know by Virtual Outlier Synthesis. In Proceedings of the International Conference on Learning Representations (ICLR)."},{"key":"e_1_3_3_1_8_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00630"},{"key":"e_1_3_3_1_9_2","volume-title":"Proceedings of the International Conference on Learning Representations (ICLR)","author":"Hendrycks Dan","year":"2017","unstructured":"Dan Hendrycks and Kevin Gimpel. 2017. A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks. In Proceedings of the International Conference on Learning Representations (ICLR)."},{"key":"e_1_3_3_1_10_2","first-page":"8759","volume-title":"Proceedings of the International Conference on Machine Learning (ICML)","author":"Hendrycks Dan","year":"2022","unstructured":"Dan Hendrycks, Mantas Mazeika, and Thomas Dietterich. 2022. Scaling Out-of-Distribution Detection for Real-World Settings. In Proceedings of the International Conference on Machine Learning (ICML). PMLR, 8759\u20138773."},{"key":"e_1_3_3_1_11_2","first-page":"18661","volume-title":"Advances in Neural Information Processing Systems (NeurIPS)","author":"Khosla Prannay","year":"2020","unstructured":"Prannay Khosla, Piotr Teterwak, Chen Wang, Aaron Sarna, Yonglong Tian, Phillip Isola, Aaron Maschinot, Ce Liu, and Dilip Krishnan. 2020. Supervised Contrastive Learning. In Advances in Neural Information Processing Systems (NeurIPS) , Vol.\u00a033. 18661\u201318673."},{"key":"e_1_3_3_1_12_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2011.6126543"},{"key":"e_1_3_3_1_13_2","first-page":"7167","volume-title":"Advances in Neural Information Processing Systems (NeurIPS)","author":"Lee Kimin","year":"2018","unstructured":"Kimin Lee, Kibok Lee, Honglak Lee, and Jinwoo Shin. 2018. A Simple Unified Framework for Detecting Out-of-Distribution Samples and Adversarial Attacks. In Advances in Neural Information Processing Systems (NeurIPS) , Vol.\u00a031. 7167\u20137177."},{"key":"e_1_3_3_1_14_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52734.2025.00953"},{"key":"e_1_3_3_1_15_2","volume-title":"Advances in Neural Information Processing Systems (NeurIPS)","author":"Liu Moru","year":"2025","unstructured":"Moru Liu, Hao Dong, Jessica\u00a0Ivy Kelly, Olga Fink, and Mario Trapp. 2025. Extremely Simple Multimodal Outlier Synthesis for Out-of-Distribution Detection and Segmentation. In Advances in Neural Information Processing Systems (NeurIPS)."},{"key":"e_1_3_3_1_16_2","first-page":"21464","volume-title":"Advances in Neural Information Processing Systems (NeurIPS)","author":"Liu Weitang","year":"2020","unstructured":"Weitang Liu, Xiaoyun Wang, John Owens, and Yixuan Li. 2020. Energy-based Out-of-Distribution Detection. In Advances in Neural Information Processing Systems (NeurIPS) , Vol.\u00a033. 21464\u201321475."},{"key":"e_1_3_3_1_17_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.02293"},{"key":"e_1_3_3_1_18_2","volume-title":"UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction","author":"McInnes Leland","year":"2018","unstructured":"Leland McInnes, John Healy, and James Melville. 2018. UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction. arxiv:https:\/\/arXiv.org\/abs\/1802.03426"},{"key":"e_1_3_3_1_19_2","volume-title":"Proceedings of the International Conference on Learning Representations (ICLR)","author":"Ming Yifei","year":"2023","unstructured":"Yifei Ming, Yiyou Sun, Ousmane Dia, and Yixuan Li. 2023. How to Exploit Hyperspherical Embeddings for Out-of-Distribution Detection?. In Proceedings of the International Conference on Learning Representations (ICLR)."},{"key":"e_1_3_3_1_20_2","first-page":"568","volume-title":"Advances in Neural Information Processing Systems (NeurIPS)","author":"Simonyan Karen","year":"2014","unstructured":"Karen Simonyan and Andrew Zisserman. 2014. Two-Stream Convolutional Networks for Action Recognition in Videos. In Advances in Neural Information Processing Systems (NeurIPS) , Vol.\u00a027. 568\u2013576."},{"key":"e_1_3_3_1_21_2","volume-title":"UCF101: A Dataset of 101 Human Actions Classes from Videos in the Wild","author":"Soomro Khurram","year":"2012","unstructured":"Khurram Soomro, Amir\u00a0Roshan Zamir, and Mubarak Shah. 2012. UCF101: A Dataset of 101 Human Actions Classes from Videos in the Wild. arxiv:https:\/\/arXiv.org\/abs\/1212.0402"},{"key":"e_1_3_3_1_22_2","first-page":"144","volume-title":"Advances in Neural Information Processing Systems (NeurIPS)","author":"Sun Yiyou","year":"2021","unstructured":"Yiyou Sun, Chuan Guo, and Yixuan Li. 2021. ReAct: Out-of-Distribution Detection With Rectified Activations. In Advances in Neural Information Processing Systems (NeurIPS) , Vol.\u00a034. 144\u2013157."},{"key":"e_1_3_3_1_23_2","first-page":"20827","volume-title":"Proceedings of the International Conference on Machine Learning (ICML)","author":"Sun Yiyou","year":"2022","unstructured":"Yiyou Sun, Yifei Ming, Xiaojin Zhu, and Yixuan Li. 2022. Out-of-Distribution Detection with Deep Nearest Neighbors. In Proceedings of the International Conference on Machine Learning (ICML). PMLR, 20827\u201320840."},{"key":"e_1_3_3_1_24_2","doi-asserted-by":"crossref","unstructured":"Duc Tri\u00a0Phan Vu Hoang Minh\u00a0Doan Jaeyeop Choi Byeongil Lee and Junghwan Oh. 2025. AADC-Net: A Multimodal Deep Learning Framework for Automatic Anomaly Detection in Real-Time Surveillance. IEEE Transactions on Instrumentation and Measurement 74 (2025) 1\u201313.","DOI":"10.1109\/TIM.2025.3551832"},{"key":"e_1_3_3_1_25_2","volume-title":"Proceedings of the International Conference on Learning Representations (ICLR)","author":"Vaze Sagar","year":"2022","unstructured":"Sagar Vaze, Kai Han, Andrea Vedaldi, and Andrew Zisserman. 2022. Open-Set Recognition: A Good Closed-Set Classifier is All You Need?. In Proceedings of the International Conference on Learning Representations (ICLR)."},{"key":"e_1_3_3_1_26_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00487"},{"key":"e_1_3_3_1_27_2","doi-asserted-by":"crossref","unstructured":"Joe\u00a0Henry Ward Jr.1963. Hierarchical Grouping to Optimize an Objective Function. J. Amer. Statist. Assoc. 58 301 (1963) 236\u2013244.","DOI":"10.1080\/01621459.1963.10500845"},{"key":"e_1_3_3_1_28_2","first-page":"23631","volume-title":"Proceedings of the International Conference on Machine Learning (ICML)","author":"Wei Hongxin","year":"2022","unstructured":"Hongxin Wei, Renchunzi Xie, Hao Cheng, Lei Feng, Bo An, and Yixuan Li. 2022. Mitigating Neural Network Overconfidence with Logit Normalization. In Proceedings of the International Conference on Machine Learning (ICML). PMLR, 23631\u201323644."},{"key":"e_1_3_3_1_29_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICIP51287.2024.10647363"},{"key":"e_1_3_3_1_30_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00819"},{"key":"e_1_3_3_1_31_2","first-page":"32598","volume-title":"Advances in Neural Information Processing Systems (NeurIPS)","author":"Yang Jingkang","year":"2022","unstructured":"Jingkang Yang, Pengyun Wang, Dejian Zou, Zitang Zhou, Kunyuan Ding, Wenxuan Peng, Haoqi Wang, Guangyao Chen, Bo Li, Yiyou Sun, et\u00a0al. 2022. OpenOOD: Benchmarking Generalized Out-of-Distribution Detection. In Advances in Neural Information Processing Systems (NeurIPS) , Vol.\u00a035. 32598\u201332611."},{"key":"e_1_3_3_1_32_2","doi-asserted-by":"crossref","unstructured":"Jingkang Yang Kaiyang Zhou Yixuan Li and Ziwei Liu. 2024. Generalized Out-of-Distribution Detection: A Survey. International Journal of Computer Vision 132 12 (2024) 5635\u20135662.","DOI":"10.1007\/s11263-024-02117-4"},{"key":"e_1_3_3_1_33_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52733.2024.02082"},{"key":"e_1_3_3_1_34_2","doi-asserted-by":"crossref","unstructured":"Hanlei Zhang Qianrui Zhou Hua Xu Jianhua Su Roberto Evans and Kai Gao. 2025. Multimodal Classification and Out-of-Distribution Detection for Multimodal Intent Understanding. IEEE Transactions on Multimedia (2025).","DOI":"10.1109\/TMM.2025.3618541"},{"key":"e_1_3_3_1_35_2","first-page":"72110","volume-title":"Advances in Neural Information Processing Systems (NeurIPS)","author":"Zheng Haotian","year":"2023","unstructured":"Haotian Zheng, Qizhou Wang, Zhen Fang, Xiaobo Xia, Feng Liu, Tongliang Liu, and Bo Han. 2023. Out-of-Distribution Detection Learning with Unreliable Out-of-Distribution Sources. In Advances in Neural Information Processing Systems (NeurIPS) , Vol.\u00a036. 72110\u201372123."}],"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":"2026-06-15T15:05:30Z","timestamp":1781535930000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3805622.3810581"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,6,15]]},"references-count":34,"alternative-id":["10.1145\/3805622.3810581","10.1145\/3805622"],"URL":"https:\/\/doi.org\/10.1145\/3805622.3810581","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"}}]}}