{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,20]],"date-time":"2026-07-20T14:16:55Z","timestamp":1784557015272,"version":"3.55.0"},"reference-count":34,"publisher":"Springer Science and Business Media LLC","issue":"7","license":[{"start":{"date-parts":[[2026,7,20]],"date-time":"2026-07-20T00:00:00Z","timestamp":1784505600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,7,20]],"date-time":"2026-07-20T00:00:00Z","timestamp":1784505600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Multimedia Systems"],"published-print":{"date-parts":[[2026,8]]},"DOI":"10.1007\/s00530-026-02542-0","type":"journal-article","created":{"date-parts":[[2026,7,20]],"date-time":"2026-07-20T13:39:19Z","timestamp":1784554759000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Precise 2D mouse pose estimation via multi-scale context and sensitive-aware loss from low illumination environment"],"prefix":"10.1007","volume":"32","author":[{"given":"Yubin","family":"Geng","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiaxin","family":"Deng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhicheng","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8153-7229","authenticated-orcid":false,"given":"Junbiao","family":"Pang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,7,20]]},"reference":[{"issue":"3","key":"2542_CR1","doi-asserted-by":"publisher","first-page":"747","DOI":"10.1038\/s41380-020-00944-8","volume":"26","author":"A Tromp","year":"2021","unstructured":"Tromp, A., Mowry, B., Giacomotto, J.: Neurexins in autism and schizophrenia\u2013a review of patient mutations, mouse models and potential future directions. Mol. Psychiatry 26(3), 747\u2013760 (2021)","journal-title":"Mol. Psychiatry"},{"issue":"9","key":"2542_CR2","doi-asserted-by":"publisher","first-page":"2902","DOI":"10.3390\/molecules27092902","volume":"27","author":"T-C Ho","year":"2022","unstructured":"Ho, T.-C., Chang, C.-C., Chan, H.-P., Chung, T.-W., Shu, C.-W., Chuang, K.-P., Duh, T.-H., Yang, M.-H., Tyan, Y.-C.: Hydrogels: properties and applications in biomedicine. Molecules 27(9), 2902 (2022)","journal-title":"Molecules"},{"issue":"3","key":"2542_CR3","doi-asserted-by":"publisher","first-page":"192","DOI":"10.1038\/s41571-022-00721-2","volume":"20","author":"J Chuprin","year":"2023","unstructured":"Chuprin, J., Buettner, H., Seedhom, M.O., Greiner, D.L., Keck, J.G., Ishikawa, F., Shultz, L.D., Brehm, M.A.: Humanized mouse models for immuno-oncology research. Nat. Rev. Clin. Oncol. 20(3), 192\u2013206 (2023)","journal-title":"Nat. Rev. Clin. Oncol."},{"issue":"4","key":"2542_CR4","first-page":"422","volume":"21","author":"M Mustapha","year":"2021","unstructured":"Mustapha, M., Taib, C.N.M.: Mptp-induced mouse model of parkinson\u2019s disease: a promising direction for therapeutic strategies. Bosn. J. Basic Med. Sci. 21(4), 422 (2021)","journal-title":"Bosn. J. Basic Med. Sci."},{"issue":"11","key":"2542_CR5","doi-asserted-by":"publisher","first-page":"3242","DOI":"10.1038\/s41596-024-01015-w","volume":"19","author":"S Lin","year":"2024","unstructured":"Lin, S., Gillis, W.F., Weinreb, C., Zeine, A., Jones, S.C., Robinson, E.M., Markowitz, J., Datta, S.R.: Characterizing the structure of mouse behavior using motion sequencing. Nat. Protoc. 19(11), 3242\u20133291 (2024)","journal-title":"Nat. Protoc."},{"key":"2542_CR6","doi-asserted-by":"crossref","unstructured":"Sheppard, K., Gardin, J., Sabnis, G.S., Peer, A., Darrell, M., Deats, S., Geuther, B., Lutz, C.M., Kumar, V.: Stride-level analysis of mouse open field behavior using deep-learning-based pose estimation. Cell Rep. 38(2), 1-26 (2022)","DOI":"10.1016\/j.celrep.2021.110231"},{"issue":"4","key":"2542_CR7","doi-asserted-by":"publisher","first-page":"542","DOI":"10.1038\/s41593-023-01288-6","volume":"26","author":"Z-P Chen","year":"2023","unstructured":"Chen, Z.-P., Wang, S., Zhao, X., Fang, W., Wang, Z., Ye, H., Wang, M.-J., Ke, L., Huang, T., Lv, P., Li, L., Xie, S., Zhu, J.-N., Hang, C., Chen, D., Liu, X., Yan, C.: Lipid-accumulated reactive astrocytes promote disease progression in epilepsy. Nat. Neurosci. 26(4), 542\u2013554 (2023)","journal-title":"Nat. Neurosci."},{"key":"2542_CR8","doi-asserted-by":"publisher","DOI":"10.3389\/fncel.2020.592710","volume":"14","author":"T Gandhi","year":"2021","unstructured":"Gandhi, T., Lee, C.C.: Neural mechanisms underlying repetitive behaviors in rodent models of autism spectrum disorders. Front. Cell. Neurosci. 14, 592710 (2021)","journal-title":"Front. Cell. Neurosci."},{"issue":"6","key":"2542_CR9","doi-asserted-by":"publisher","first-page":"1389","DOI":"10.1007\/s11263-023-01756-3","volume":"131","author":"T Li","year":"2023","unstructured":"Li, T., Severson, K.S., Wang, F., Dunn, T.W.: Improved 3d markerless mouse pose estimation using temporal semi-supervision. Int. J. Comput. Vision 131(6), 1389\u20131405 (2023)","journal-title":"Int. J. Comput. Vision"},{"issue":"1","key":"2542_CR10","doi-asserted-by":"publisher","first-page":"11","DOI":"10.1007\/s10462-023-10631-z","volume":"57","author":"R Archana","year":"2024","unstructured":"Archana, R., Jeevaraj, P.E.: Deep learning models for digital image processing: a review. Artif. Intell. Rev. 57(1), 11 (2024)","journal-title":"Artif. Intell. Rev."},{"issue":"2","key":"2542_CR11","doi-asserted-by":"publisher","first-page":"531","DOI":"10.3390\/s25020531","volume":"25","author":"M Trigka","year":"2025","unstructured":"Trigka, M., Dritsas, E.: A comprehensive survey of deep learning approaches in image processing. Sensors 25(2), 531 (2025)","journal-title":"Sensors"},{"issue":"1","key":"2542_CR12","doi-asserted-by":"publisher","first-page":"117","DOI":"10.1038\/s41592-018-0234-5","volume":"16","author":"TD Pereira","year":"2019","unstructured":"Pereira, T.D., Aldarondo, D.E., Willmore, L., Kislin, M., Wang, S.S.-H., Murthy, M., Shaevitz, J.W.: Fast animal pose estimation using deep neural networks. Nat. Methods 16(1), 117\u2013125 (2019)","journal-title":"Nat. Methods"},{"issue":"1","key":"2542_CR13","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3603618","volume":"56","author":"C Zheng","year":"2023","unstructured":"Zheng, C., Wu, W., Chen, C., Yang, T., Zhu, S., Shen, J., Kehtarnavaz, N., Shah, M.: Deep learning-based human pose estimation: a survey. ACM Comput. Surv. 56(1), 1\u201337 (2023)","journal-title":"ACM Comput. Surv."},{"issue":"4","key":"2542_CR14","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3524497","volume":"55","author":"W Liu","year":"2022","unstructured":"Liu, W., Bao, Q., Sun, Y., Mei, T.: Recent advances of monocular 2d and 3d human pose estimation: a deep learning perspective. ACM Comput. Surv. 55(4), 1\u201341 (2022)","journal-title":"ACM Comput. Surv."},{"issue":"9","key":"2542_CR15","doi-asserted-by":"publisher","first-page":"1281","DOI":"10.1038\/s41593-018-0209-y","volume":"21","author":"A Mathis","year":"2018","unstructured":"Mathis, A., Mamidanna, P., Cury, K.M., Abe, T., Murthy, V.N., Mathis, M.W., Bethge, M.: Deeplabcut: markerless pose estimation of user-defined body parts with deep learning. Nat. Neurosci. 21(9), 1281\u20131289 (2018)","journal-title":"Nat. Neurosci."},{"issue":"5","key":"2542_CR16","doi-asserted-by":"publisher","first-page":"2787","DOI":"10.1109\/TCSVT.2021.3098497","volume":"32","author":"F Zhou","year":"2021","unstructured":"Zhou, F., Jiang, Z., Liu, Z., Chen, F., Chen, L., Tong, L., Yang, Z., Wang, H., Fei, M., Li, L., Zhou, H.: Structured context enhancement network for mouse pose estimation. IEEE Trans. Circuits Syst. Video Technol. 32(5), 2787\u20132801 (2021)","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"2542_CR17","doi-asserted-by":"crossref","unstructured":"Ai, Y., Qi, Y., Tan, R.T.: Domain-adaptive 2d human pose estimation via dual teachers in extremely low-light conditions, ECCV (2024)","DOI":"10.1007\/978-3-031-72970-6_13"},{"issue":"9","key":"2542_CR18","doi-asserted-by":"publisher","first-page":"11547","DOI":"10.1007\/s11042-017-5091-1","volume":"77","author":"F Courtemanche","year":"2018","unstructured":"Courtemanche, F., L\u00e9ger, P.-M., Dufresne, A., Fredette, M., Labont\u00e9-LeMoyne, \u00c9., S\u00e9n\u00e9cal, S.: Physiological heatmaps: a tool for visualizing users\u2019 emotional reactions. Multim. Tools Appl. 77(9), 11547\u201311574 (2018)","journal-title":"Multim. Tools Appl."},{"issue":"4","key":"2542_CR19","doi-asserted-by":"publisher","first-page":"496","DOI":"10.1038\/s41592-022-01443-0","volume":"19","author":"J Lauer","year":"2022","unstructured":"Lauer, J., Zhou, M., Ye, S., Menegas, W., Schneider, S., Nath, T., Rahman, M.M., Di Santo, V., Soberanes, D., Feng, G., Murthy, V.N., Lauder, G., Dulac, C., Mathis, M.W., Mathis, A.: Multi-animal pose estimation, identification and tracking with deeplabcut. Nat. Methods 19(4), 496\u2013504 (2022)","journal-title":"Nat. Methods"},{"key":"2542_CR20","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/TIM.2025.3551854","volume":"74","author":"M Yu","year":"2025","unstructured":"Yu, M., Dong, H., You, R., Liang, S., Zhang, Q., Ge, Y., Lin, M., Xu, Z.: Yolo-mousepose: A novel framework and dataset for mouse pose estimation from a top-down view. IEEE Trans. Instrum. Meas. 74, 1\u201319 (2025). https:\/\/doi.org\/10.1109\/TIM.2025.3551854","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"2542_CR21","unstructured":"Tran, D., Ray, J., Shou, Z., Chang, S.-F., Paluri, M.: Convnet architecture search for spatiotemporal feature learning. (2017). arXiv:1708.05038"},{"key":"2542_CR22","doi-asserted-by":"crossref","unstructured":"Wei, S.-E., Ramakrishna, V., Kanade, T., Sheikh, Y.: Convolutional pose machines. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 4724\u20134732 (2016)","DOI":"10.1109\/CVPR.2016.511"},{"key":"2542_CR23","doi-asserted-by":"crossref","unstructured":"Newell, A., Yang, K., Deng, J.: Stacked hourglass networks for human pose estimation. In: European Conference on Computer Vision, pp. 483\u2013499. Springer (2016)","DOI":"10.1007\/978-3-319-46484-8_29"},{"key":"2542_CR24","doi-asserted-by":"crossref","unstructured":"Sun, K., Xiao, B., Liu, D., Wang, J.: Deep high-resolution representation learning for human pose estimation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 5693\u20135703 (2019)","DOI":"10.1109\/CVPR.2019.00584"},{"key":"2542_CR25","doi-asserted-by":"crossref","unstructured":"Pang, J., Wan, S.: Toward precise point location in mouse pose estimation by multi-scale supervised network. In: 2021 China Automation Congress (CAC), pp. 5262\u20135267. IEEE (2021)","DOI":"10.1109\/CAC53003.2021.9727658"},{"key":"2542_CR26","doi-asserted-by":"crossref","unstructured":"Toshev, A., Szegedy, C.: Deeppose: Human pose estimation via deep neural networks. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1653\u20131660. (2014)","DOI":"10.1109\/CVPR.2014.214"},{"issue":"4","key":"2542_CR27","doi-asserted-by":"publisher","first-page":"1186","DOI":"10.1109\/TCE.2023.3247901","volume":"69","author":"Z Guo","year":"2023","unstructured":"Guo, Z., Chen, J., He, T., Wang, W., Abbas, H., Lv, Z.: Ds-cnn: dual-stream convolutional neural networks-based heart sound classification for wearable devices. IEEE Trans. Consum. Electron. 69(4), 1186\u20131194 (2023)","journal-title":"IEEE Trans. Consum. Electron."},{"key":"2542_CR28","doi-asserted-by":"publisher","first-page":"3706","DOI":"10.52202\/075280-0164","volume":"36","author":"Z Sun","year":"2023","unstructured":"Sun, Z., Yang, Y.: Difusco: graph-based diffusion solvers for combinatorial optimization. Adv. Neural. Inf. Process. Syst. 36, 3706\u20133731 (2023)","journal-title":"Adv. Neural. Inf. Process. Syst."},{"key":"2542_CR29","unstructured":"Goffinet, J., Min, Y., Tomasi, C., Carlson, D.E.: Pose splatter: a 3d gaussian splatting model for quantifying animal pose and appearance. (2025). arXiv:2505.18342"},{"key":"2542_CR30","doi-asserted-by":"publisher","first-page":"95709","DOI":"10.7554\/eLife.95709","volume":"13","author":"G Tang","year":"2025","unstructured":"Tang, G., Han, Y., Sun, X., Zhang, R., Han, M.-H., Liu, Q., Wei, P.: Anti-drift pose tracker (adpt), a transformer-based network for robust animal pose estimation cross-species. Elife 13, 95709 (2025)","journal-title":"Elife"},{"key":"2542_CR31","unstructured":"Artacho, B., Savakis, A.: Omnipose: a multi-scale framework for multi-person pose estimation, (2021). arXiv:2103.10180"},{"key":"2542_CR32","unstructured":"Khanam, R., Hussain, M.: Yolov11: an overview of the key architectural enhancements. (2024). arXiv:2410.17725"},{"issue":"10","key":"2542_CR33","doi-asserted-by":"publisher","first-page":"11147","DOI":"10.1007\/s10489-021-03089-5","volume":"52","author":"X Zhou","year":"2022","unstructured":"Zhou, X., Geng, Y.-A., Yu, H., Li, Q., Xu, L., Yao, W., Zheng, D., Zhang, Y.: Lightnet+: a dual-source lightning forecasting network with bi-direction spatiotemporal transformation. Appl. Intell. 52(10), 11147\u201311159 (2022)","journal-title":"Appl. Intell."},{"key":"2542_CR34","doi-asserted-by":"crossref","unstructured":"Chen, S., Zhang, Y., Huang, S., Yi, R., Fan, K., Zhang, R., Chen, P., Wang, J., Ding, S., Ma, L.: Sdpose: Tokenized pose estimation via circulation-guide self-distillation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 1082\u20131090 (2024)","DOI":"10.1109\/CVPR52733.2024.00109"}],"container-title":["Multimedia Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00530-026-02542-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00530-026-02542-0","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00530-026-02542-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,20]],"date-time":"2026-07-20T13:39:22Z","timestamp":1784554762000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00530-026-02542-0"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7,20]]},"references-count":34,"journal-issue":{"issue":"7","published-print":{"date-parts":[[2026,8]]}},"alternative-id":["2542"],"URL":"https:\/\/doi.org\/10.1007\/s00530-026-02542-0","relation":{},"ISSN":["0942-4962","1432-1882"],"issn-type":[{"value":"0942-4962","type":"print"},{"value":"1432-1882","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,7,20]]},"assertion":[{"value":"10 March 2026","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"2 July 2026","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"20 July 2026","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"The authors declare no conflict of interest.","order":1,"name":"Ethics","label":"Conflict of interest","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"This article does not contain any studies with human participants or animals performed by any of the authors.","order":2,"name":"Ethics","label":"Ethical approval","group":{"name":"EthicsHeading","label":"Declarations"}}],"article-number":"461"}}