{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,20]],"date-time":"2026-01-20T13:33:00Z","timestamp":1768915980003,"version":"3.49.0"},"publisher-location":"Cham","reference-count":60,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031729690","type":"print"},{"value":"9783031729706","type":"electronic"}],"license":[{"start":{"date-parts":[[2024,11,23]],"date-time":"2024-11-23T00:00:00Z","timestamp":1732320000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,11,23]],"date-time":"2024-11-23T00:00:00Z","timestamp":1732320000000},"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":[],"published-print":{"date-parts":[[2025]]},"DOI":"10.1007\/978-3-031-72970-6_13","type":"book-chapter","created":{"date-parts":[[2024,11,22]],"date-time":"2024-11-22T10:53:08Z","timestamp":1732272788000},"page":"221-239","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Domain-Adaptive 2D Human Pose Estimation via\u00a0Dual Teachers in\u00a0Extremely Low-Light Conditions"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0009-0005-2336-4813","authenticated-orcid":false,"given":"Yihao","family":"Ai","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0009-0007-4197-947X","authenticated-orcid":false,"given":"Yifei","family":"Qi","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0127-2281","authenticated-orcid":false,"given":"Bo","family":"Wang","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9830-0081","authenticated-orcid":false,"given":"Yu","family":"Cheng","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0057-1404","authenticated-orcid":false,"given":"Xinchao","family":"Wang","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7532-6919","authenticated-orcid":false,"given":"Robby T.","family":"Tan","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,11,23]]},"reference":[{"key":"13_CR1","doi-asserted-by":"crossref","unstructured":"Cai, Y., Bian, H., Lin, J., Wang, H., Timofte, R., Zhang, Y.: Retinexformer: one-stage retinex-based transformer for low-light image enhancement. arXiv preprint arXiv:2303.06705 (2023)","DOI":"10.1109\/ICCV51070.2023.01149"},{"key":"13_CR2","doi-asserted-by":"crossref","unstructured":"Cao, J., Tang, H., Fang, H.S., Shen, X., Lu, C., Tai, Y.W.: Cross-domain adaptation for animal pose estimation. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 9498\u20139507 (2019)","DOI":"10.1109\/ICCV.2019.00959"},{"issue":"1","key":"13_CR3","doi-asserted-by":"publisher","first-page":"172","DOI":"10.1109\/TPAMI.2019.2929257","volume":"43","author":"Z Cao","year":"2019","unstructured":"Cao, Z., Hidalgo, G., Simon, T., Wei, S.E., Sheikh, Y.: OpenPose: realtime multi-person 2D pose estimation using part affinity fields. IEEE Trans. Pattern Anal. Mach. Intell. 43(1), 172\u2013186 (2019)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"12","key":"13_CR4","doi-asserted-by":"publisher","first-page":"3431","DOI":"10.1109\/TIP.2011.2157513","volume":"20","author":"T Celik","year":"2011","unstructured":"Celik, T., Tjahjadi, T.: Contextual and variational contrast enhancement. IEEE Trans. Image Process. 20(12), 3431\u20133441 (2011)","journal-title":"IEEE Trans. Image Process."},{"key":"13_CR5","doi-asserted-by":"crossref","unstructured":"Chen, Y., Wang, Z., Peng, Y., Zhang, Z., Yu, G., Sun, J.: Cascaded pyramid network for multi-person pose estimation. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 7103\u20137112 (2018)","DOI":"10.1109\/CVPR.2018.00742"},{"key":"13_CR6","doi-asserted-by":"crossref","unstructured":"Cheng, B., Xiao, B., Wang, J., Shi, H., Huang, T.S., Zhang, L.: HigherHRNet: scale-aware representation learning for bottom-up human pose estimation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 5386\u20135395 (2020)","DOI":"10.1109\/CVPR42600.2020.00543"},{"issue":"2","key":"13_CR7","doi-asserted-by":"publisher","first-page":"158","DOI":"10.1016\/j.dsp.2003.07.002","volume":"14","author":"HD Cheng","year":"2004","unstructured":"Cheng, H.D., Shi, X.: A simple and effective histogram equalization approach to image enhancement. Digit. Signal Process. 14(2), 158\u2013170 (2004)","journal-title":"Digit. Signal Process."},{"key":"13_CR8","doi-asserted-by":"publisher","first-page":"109403","DOI":"10.1016\/j.patcog.2023.109403","volume":"139","author":"Y Cheng","year":"2023","unstructured":"Cheng, Y., Ai, Y., Wang, B., Wang, X., Tan, R.T.: Bottom-up 2D pose estimation via dual anatomical centers for small-scale persons. Pattern Recogn. 139, 109403 (2023)","journal-title":"Pattern Recogn."},{"key":"13_CR9","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/TIM.2020.3043872","volume":"70","author":"V Crescitelli","year":"2020","unstructured":"Crescitelli, V., Kosuge, A., Oshima, T.: POISON: human pose estimation in insufficient lighting conditions using sensor fusion. IEEE Trans. Instrum. Meas. 70, 1\u20138 (2020)","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"13_CR10","doi-asserted-by":"crossref","unstructured":"Crescitelli, V., Kosuge, A., Oshima, T.: An RGB\/infra-red camera fusion approach for multi-person pose estimation in low light environments. In: 2020 IEEE Sensors Applications Symposium (SAS), pp.\u00a01\u20136. IEEE (2020)","DOI":"10.1109\/SAS48726.2020.9220059"},{"key":"13_CR11","doi-asserted-by":"crossref","unstructured":"Desmarais, Y., Mottet, D., Slangen, P., Montesinos, P.: A review of 3D human pose estimation algorithms for markerless motion capture. Comput. Vision Image Underst. 103275 (2021)","DOI":"10.1016\/j.cviu.2021.103275"},{"key":"13_CR12","doi-asserted-by":"crossref","unstructured":"Dong, H., et al.: Towards multi-pose guided virtual try-on network. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 9026\u20139035 (2019)","DOI":"10.1109\/ICCV.2019.00912"},{"issue":"1","key":"13_CR13","first-page":"2096","volume":"17","author":"Y Ganin","year":"2016","unstructured":"Ganin, Y., et al.: Domain-adversarial training of neural networks. J. Mach. Learn. Res. 17(1), 2096\u20132130 (2016)","journal-title":"J. Mach. Learn. Res."},{"key":"13_CR14","doi-asserted-by":"crossref","unstructured":"Geng, Z., Sun, K., Xiao, B., Zhang, Z., Wang, J.: Bottom-up human pose estimation via disentangled keypoint regression. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 14676\u201314686 (2021)","DOI":"10.1109\/CVPR46437.2021.01444"},{"key":"13_CR15","doi-asserted-by":"crossref","unstructured":"Guo, X.: LIME: a method for low-light image enhancement. In: Proceedings of the 24th ACM International Conference on Multimedia, pp. 87\u201391 (2016)","DOI":"10.1145\/2964284.2967188"},{"key":"13_CR16","doi-asserted-by":"publisher","first-page":"6424","DOI":"10.1109\/TIP.2022.3184848","volume":"31","author":"Z Han","year":"2022","unstructured":"Han, Z., Sun, H., Yin, Y.: Learning transferable parameters for unsupervised domain adaptation. IEEE Trans. Image Process. 31, 6424\u20136439 (2022)","journal-title":"IEEE Trans. Image Process."},{"key":"13_CR17","doi-asserted-by":"crossref","unstructured":"He, K., Gkioxari, G., Doll\u00e1r, P., Girshick, R.: Mask R-CNN. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 2961\u20132969 (2017)","DOI":"10.1109\/ICCV.2017.322"},{"key":"13_CR18","doi-asserted-by":"crossref","unstructured":"Hosang, J., Benenson, R., Schiele, B.: Learning non-maximum suppression. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 4507\u20134515 (2017)","DOI":"10.1109\/CVPR.2017.685"},{"key":"13_CR19","doi-asserted-by":"crossref","unstructured":"Huang, L., et al.: Semi-supervised 2D human pose estimation driven by position inconsistency pseudo label correction module. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 693\u2013703 (2023)","DOI":"10.1109\/CVPR52729.2023.00074"},{"key":"13_CR20","doi-asserted-by":"crossref","unstructured":"Huang, X., Belongie, S.: Arbitrary style transfer in real-time with adaptive instance normalization. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 1501\u20131510 (2017)","DOI":"10.1109\/ICCV.2017.167"},{"key":"13_CR21","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"443","DOI":"10.1007\/978-3-031-20065-6_26","volume-title":"Computer Vision \u2013 ECCV 2022","author":"J Jiang","year":"2022","unstructured":"Jiang, J., et al.: AvatarPoser: articulated full-body pose tracking from sparse motion sensing. In: Avidan, S., Brostow, G., Ciss\u00e9, M., Farinella, G.M., Hassner, T. (eds.) ECCV 2022. LNCS, vol. 13665, pp. 443\u2013460. Springer, Cham (2022). https:\/\/doi.org\/10.1007\/978-3-031-20065-6_26"},{"key":"13_CR22","doi-asserted-by":"crossref","unstructured":"Jiang, J., Ji, Y., Wang, X., Liu, Y., Wang, J., Long, M.: Regressive domain adaptation for unsupervised keypoint detection. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 6780\u20136789 (2021)","DOI":"10.1109\/CVPR46437.2021.00671"},{"issue":"9","key":"13_CR23","doi-asserted-by":"publisher","first-page":"6125","DOI":"10.1109\/TCSVT.2022.3158676","volume":"32","author":"R Jin","year":"2022","unstructured":"Jin, R., Zhang, J., Yang, J., Tao, D.: Multibranch adversarial regression for domain adaptative hand pose estimation. IEEE Trans. Circuits Syst. Video Technol. 32(9), 6125\u20136136 (2022)","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"13_CR24","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"404","DOI":"10.1007\/978-3-031-19836-6_23","volume-title":"Computer Vision \u2013 ECCV 2022","author":"Y Jin","year":"2022","unstructured":"Jin, Y., Yang, W., Tan, R.T.: Unsupervised night image enhancement: when layer decomposition meets light-effects suppression. In: Avidan, S., Brostow, G., Ciss\u00e9, M., Farinella, G.M., Hassner, T. (eds.) ECCV 2022. LNCS, vol. 13697, pp. 404\u2013421. Springer, Cham (2022). https:\/\/doi.org\/10.1007\/978-3-031-19836-6_23"},{"key":"13_CR25","doi-asserted-by":"crossref","unstructured":"Kennerley, M., Wang, J.G., Veeravalli, B., Tan, R.T.: 2PCNet: two-phase consistency training for day-to-night unsupervised domain adaptive object detection. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 11484\u201311493 (2023)","DOI":"10.1109\/CVPR52729.2023.01105"},{"key":"13_CR26","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"603","DOI":"10.1007\/978-3-031-19827-4_35","volume-title":"Computer Vision \u2013 ECCV 2022","author":"D Kim","year":"2022","unstructured":"Kim, D., Wang, K., Saenko, K., Betke, M., Sclaroff, S.: A unified framework for domain adaptive pose estimation. In: Avidan, S., Brostow, G., Ciss\u00e9, M., Farinella, G.M., Hassner, T. (eds.) ECCV 2022. LNCS, vol. 13693, pp. 603\u2013620. Springer, Cham (2022). https:\/\/doi.org\/10.1007\/978-3-031-19827-4_35"},{"key":"13_CR27","doi-asserted-by":"crossref","unstructured":"Kocabas, M., Karagoz, S., Akbas, E.: MultiPoseNet: fast multi-person pose estimation using pose residual network. In: Proceedings of the European Conference on Computer Vision (ECCV), pp. 417\u2013433 (2018)","DOI":"10.1007\/978-3-030-01252-6_26"},{"issue":"1\u20132","key":"13_CR28","doi-asserted-by":"publisher","first-page":"83","DOI":"10.1002\/nav.3800020109","volume":"2","author":"HW Kuhn","year":"1955","unstructured":"Kuhn, H.W.: The Hungarian method for the assignment problem. Naval Res. Logist. Q. 2(1\u20132), 83\u201397 (1955)","journal-title":"Naval Res. Logist. Q."},{"key":"13_CR29","doi-asserted-by":"crossref","unstructured":"Lee, S., et al.: Human pose estimation in extremely low-light conditions. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2023)","DOI":"10.1109\/CVPR52729.2023.00075"},{"key":"13_CR30","doi-asserted-by":"crossref","unstructured":"Li, C., Lee, G.H.: From synthetic to real: unsupervised domain adaptation for animal pose estimation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 1482\u20131491 (2021)","DOI":"10.1109\/CVPR46437.2021.00153"},{"key":"13_CR31","doi-asserted-by":"crossref","unstructured":"Li, J., Wang, C., Zhu, H., Mao, Y., Fang, H.S., Lu, C.: CrowdPose: efficient crowded scenes pose estimation and a new benchmark. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 10863\u201310872 (2019)","DOI":"10.1109\/CVPR.2019.01112"},{"issue":"6","key":"13_CR32","doi-asserted-by":"publisher","first-page":"2828","DOI":"10.1109\/TIP.2018.2810539","volume":"27","author":"M Li","year":"2018","unstructured":"Li, M., Liu, J., Yang, W., Sun, X., Guo, Z.: Structure-revealing low-light image enhancement via robust retinex model. IEEE Trans. Image Process. 27(6), 2828\u20132841 (2018)","journal-title":"IEEE Trans. Image Process."},{"key":"13_CR33","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"351","DOI":"10.1007\/978-3-031-19827-4_21","volume-title":"Computer Vision \u2013 ECCV 2022","author":"H Lin","year":"2022","unstructured":"Lin, H., et al.: Prototype-guided continual adaptation for class-incremental unsupervised domain adaptation. In: Avidan, S., Brostow, G., Ciss\u00e9, M., Farinella, G.M., Hassner, T. (eds.) ECCV 2022. LNCS, vol. 13693, pp. 351\u2013368. Springer, Cham (2022). https:\/\/doi.org\/10.1007\/978-3-031-19827-4_21"},{"key":"13_CR34","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"740","DOI":"10.1007\/978-3-319-10602-1_48","volume-title":"Computer Vision \u2013 ECCV 2014","author":"T-Y Lin","year":"2014","unstructured":"Lin, T.-Y., Maire, M., Belongie, S., Hays, J., Perona, P., Ramanan, D., Doll\u00e1r, P., Zitnick, C.L.: Microsoft COCO: common objects in context. In: Fleet, D., Pajdla, T., Schiele, B., Tuytelaars, T. (eds.) ECCV 2014. LNCS, vol. 8693, pp. 740\u2013755. Springer, Cham (2014). https:\/\/doi.org\/10.1007\/978-3-319-10602-1_48"},{"key":"13_CR35","doi-asserted-by":"crossref","unstructured":"Moran, S., Marza, P., McDonagh, S., Parisot, S., Slabaugh, G.: DeepLPF: deep local parametric filters for image enhancement. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 12826\u201312835 (2020)","DOI":"10.1109\/CVPR42600.2020.01284"},{"key":"13_CR36","doi-asserted-by":"crossref","unstructured":"Mu, J., Qiu, W., Hager, G.D., Yuille, A.L.: Learning from synthetic animals. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 12386\u201312395 (2020)","DOI":"10.1109\/CVPR42600.2020.01240"},{"key":"13_CR37","unstructured":"Newell, A., Huang, Z., Deng, J.: Associative embedding: end-to-end learning for joint detection and grouping. Adv. Neural Inf. Process. Syst. 30 (2017)"},{"key":"13_CR38","doi-asserted-by":"crossref","unstructured":"Peng, Q., Zheng, C., Chen, C.: Source-free domain adaptive human pose estimation. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 4826\u20134836 (2023)","DOI":"10.1109\/ICCV51070.2023.00445"},{"key":"13_CR39","doi-asserted-by":"crossref","unstructured":"Punnappurath, A., Abuolaim, A., Abdelhamed, A., Levinshtein, A., Brown, M.S.: Day-to-night image synthesis for training nighttime neural ISPS. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 10769\u201310778 (2022)","DOI":"10.1109\/CVPR52688.2022.01050"},{"issue":"1","key":"13_CR40","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s13640-016-0138-1","volume":"2016","author":"S Rahman","year":"2016","unstructured":"Rahman, S., Rahman, M.M., Abdullah-Al-Wadud, M., Al-Quaderi, G.D., Shoyaib, M.: An adaptive gamma correction for image enhancement. EURASIP J. Image Video Process. 2016(1), 1\u201313 (2016)","journal-title":"EURASIP J. Image Video Process."},{"key":"13_CR41","doi-asserted-by":"crossref","unstructured":"Raychaudhuri, D.S., Ta, C.K., Dutta, A., Lal, R., Roy-Chowdhury, A.K.: Prior-guided source-free domain adaptation for human pose estimation. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 14996\u201315006 (2023)","DOI":"10.1109\/ICCV51070.2023.01377"},{"key":"13_CR42","doi-asserted-by":"crossref","unstructured":"Sharma, A., Tan, R.T.: Nighttime visibility enhancement by increasing the dynamic range and suppression of light effects. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 11977\u201311986 (2021)","DOI":"10.1109\/CVPR46437.2021.01180"},{"key":"13_CR43","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":"13_CR44","unstructured":"Tarvainen, A., Valpola, H.: Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results. Adv. Neural Inf. Process. Syst. 30 (2017)"},{"key":"13_CR45","unstructured":"Tian, Z., Chen, H., Shen, C.: DirectPose: direct end-to-end multi-person pose estimation. arXiv preprint arXiv:1911.07451 (2019)"},{"key":"13_CR46","doi-asserted-by":"crossref","unstructured":"Vu, T.H., Jain, H., Bucher, M., Cord, M., P\u00e9rez, P.: ADVENT: adversarial entropy minimization for domain adaptation in semantic segmentation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 2517\u20132526 (2019)","DOI":"10.1109\/CVPR.2019.00262"},{"key":"13_CR47","doi-asserted-by":"crossref","unstructured":"Wang, D., Zhang, S.: Contextual instance decoupling for robust multi-person pose estimation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 11060\u201311068 (2022)","DOI":"10.1109\/CVPR52688.2022.01078"},{"key":"13_CR48","unstructured":"Wang, D., Zhang, S., Hua, G.: Robust pose estimation in crowded scenes with direct pose-level inference. Adv. Neural Inf. Process. Syst. 34 (2021)"},{"key":"13_CR49","doi-asserted-by":"crossref","unstructured":"Wang, Q., Fink, O., Van\u00a0Gool, L., Dai, D.: Continual test-time domain adaptation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 7201\u20137211 (2022)","DOI":"10.1109\/CVPR52688.2022.00706"},{"key":"13_CR50","doi-asserted-by":"crossref","unstructured":"Wang, R., Zhang, Q., Fu, C.W., Shen, X., Zheng, W.S., Jia, J.: Underexposed photo enhancement using deep illumination estimation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 6849\u20136857 (2019)","DOI":"10.1109\/CVPR.2019.00701"},{"issue":"9","key":"13_CR51","doi-asserted-by":"publisher","first-page":"3538","DOI":"10.1109\/TIP.2013.2261309","volume":"22","author":"S Wang","year":"2013","unstructured":"Wang, S., Zheng, J., Hu, H.M., Li, B.: Naturalness preserved enhancement algorithm for non-uniform illumination images. IEEE Trans. Image Process. 22(9), 3538\u20133548 (2013)","journal-title":"IEEE Trans. Image Process."},{"key":"13_CR52","doi-asserted-by":"crossref","unstructured":"Wang, Y., Wan, R., Yang, W., Li, H., Chau, L.P., Kot, A.: Low-light image enhancement with normalizing flow. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol.\u00a036, pp. 2604\u20132612 (2022)","DOI":"10.1609\/aaai.v36i3.20162"},{"key":"13_CR53","doi-asserted-by":"crossref","unstructured":"Wei, K., Fu, Y., Yang, J., Huang, H.: A physics-based noise formation model for extreme low-light raw denoising. In: IEEE Conference on Computer Vision and Pattern Recognition (2020)","DOI":"10.1109\/CVPR42600.2020.00283"},{"issue":"11","key":"13_CR54","first-page":"8520","volume":"44","author":"K Wei","year":"2021","unstructured":"Wei, K., Fu, Y., Zheng, Y., Yang, J.: Physics-based noise modeling for extreme low-light photography. IEEE Trans. Pattern Anal. Mach. Intell. 44(11), 8520\u20138537 (2021)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"13_CR55","doi-asserted-by":"crossref","unstructured":"Weng, C.Y., Curless, B., Kemelmacher-Shlizerman, I.: Photo wake-up: 3D character animation from a single photo. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 5908\u20135917 (2019)","DOI":"10.1109\/CVPR.2019.00606"},{"key":"13_CR56","doi-asserted-by":"crossref","unstructured":"Xiao, B., Wu, H., Wei, Y.: Simple baselines for human pose estimation and tracking. In: Proceedings of the European Conference on Computer Vision (ECCV), pp. 466\u2013481 (2018)","DOI":"10.1007\/978-3-030-01231-1_29"},{"key":"13_CR57","doi-asserted-by":"crossref","unstructured":"Xie, R., Wang, C., Zeng, W., Wang, Y.: An empirical study of the collapsing problem in semi-supervised 2D human pose estimation. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 11240\u201311249 (2021)","DOI":"10.1109\/ICCV48922.2021.01105"},{"key":"13_CR58","doi-asserted-by":"crossref","unstructured":"Xue, N., Wu, T., Xia, G.S., Zhang, L.: Learning local-global contextual adaptation for multi-person pose estimation. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2022)","DOI":"10.1109\/CVPR52688.2022.01272"},{"key":"13_CR59","doi-asserted-by":"crossref","unstructured":"Yan, S., Xiong, Y., Lin, D.: Spatial temporal graph convolutional networks for skeleton-based action recognition. In: Thirty-Second AAAI Conference on Artificial Intelligence (2018)","DOI":"10.1609\/aaai.v32i1.12328"},{"key":"13_CR60","doi-asserted-by":"crossref","unstructured":"Zhang, S.H., et al.: Pose2Seg: detection free human instance segmentation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 889\u2013898 (2019)","DOI":"10.1109\/CVPR.2019.00098"}],"container-title":["Lecture Notes in Computer Science","Computer Vision \u2013 ECCV 2024"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-72970-6_13","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,22]],"date-time":"2024-11-22T11:13:07Z","timestamp":1732273987000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-72970-6_13"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,11,23]]},"ISBN":["9783031729690","9783031729706"],"references-count":60,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-72970-6_13","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,11,23]]},"assertion":[{"value":"23 November 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ECCV","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"European Conference on Computer Vision","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Milan","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Italy","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"29 September 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"4 October 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"eccv2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/eccv2024.ecva.net\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}