{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,8]],"date-time":"2026-05-08T16:40:54Z","timestamp":1778258454696,"version":"3.51.4"},"publisher-location":"Cham","reference-count":48,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031727634","type":"print"},{"value":"9783031727641","type":"electronic"}],"license":[{"start":{"date-parts":[[2024,10,25]],"date-time":"2024-10-25T00:00:00Z","timestamp":1729814400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,10,25]],"date-time":"2024-10-25T00:00:00Z","timestamp":1729814400000},"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\/978-3-031-72764-1_7","type":"book-chapter","created":{"date-parts":[[2024,10,24]],"date-time":"2024-10-24T14:03:10Z","timestamp":1729778590000},"page":"108-125","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Representation Enhancement-Stabilization: Reducing Bias-Variance of\u00a0Domain Generalization"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5862-3126","authenticated-orcid":false,"given":"Wei","family":"Huang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7386-0026","authenticated-orcid":false,"given":"Yilei","family":"Shi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3953-585X","authenticated-orcid":false,"given":"Zhitong","family":"Xiong","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5530-3613","authenticated-orcid":false,"given":"Xiao Xiang","family":"Zhu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,10,25]]},"reference":[{"key":"7_CR1","unstructured":"Albuquerque, I., Naik, N., Li, J., Keskar, N., Socher, R.: Improving out-of-distribution generalization via multi-task self-supervised pretraining. arXiv preprint arXiv:2003.13525 (2020)"},{"key":"7_CR2","first-page":"8265","volume":"35","author":"D Arpit","year":"2022","unstructured":"Arpit, D., Wang, H., Zhou, Y., Xiong, C.: Ensemble of averages: Improving model selection and boosting performance in domain generalization. Adv. Neural. Inf. Process. Syst. 35, 8265\u20138277 (2022)","journal-title":"Adv. Neural. Inf. Process. Syst."},{"key":"7_CR3","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"472","DOI":"10.1007\/978-3-030-01270-0_28","volume-title":"Computer Vision \u2013 ECCV 2018","author":"S Beery","year":"2018","unstructured":"Beery, S., Van Horn, G., Perona, P.: Recognition in terra incognita. In: Ferrari, V., Hebert, M., Sminchisescu, C., Weiss, Y. (eds.) ECCV 2018. LNCS, vol. 11220, pp. 472\u2013489. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-030-01270-0_28"},{"key":"7_CR4","first-page":"22405","volume":"34","author":"J Cha","year":"2021","unstructured":"Cha, J., et al.: SWAD: domain generalization by seeking flat minima. Adv. Neural. Inf. Process. Syst. 34, 22405\u201322418 (2021)","journal-title":"Adv. Neural. Inf. Process. Syst."},{"key":"7_CR5","series-title":"LNCS","doi-asserted-by":"publisher","first-page":"440","DOI":"10.1007\/978-3-031-20050-2_26","volume-title":"ECCV 2022","author":"J Cha","year":"2022","unstructured":"Cha, J., Lee, K., Park, S., Chun, S.: Domain generalization by mutual-information regularization with pre-trained models. In: Avidan, S., Brostow, G., Ciss\u00e9, M., Farinella, G.M., Hassner, T. (eds.) ECCV 2022. LNCS, vol. 13683, pp. 440\u2013457. Springer, Cham (2022). https:\/\/doi.org\/10.1007\/978-3-031-20050-2_26"},{"key":"7_CR6","doi-asserted-by":"crossref","unstructured":"Chen, C., Li, J., Han, X., Liu, X., Yu, Y.: Compound domain generalization via meta-knowledge encoding. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 7119\u20137129 (2022)","DOI":"10.1109\/CVPR52688.2022.00698"},{"key":"7_CR7","doi-asserted-by":"crossref","unstructured":"Chen, J., Gao, Z., Wu, X., Luo, J.: Meta-causal learning for single domain generalization. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 7683\u20137692 (2023)","DOI":"10.1109\/CVPR52729.2023.00742"},{"key":"7_CR8","doi-asserted-by":"crossref","unstructured":"Cubuk, E.D., Zoph, B., Shlens, J., Le, Q.V.: Randaugment: practical automated data augmentation with a reduced search space. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition Workshops, pp. 702\u2013703 (2020)","DOI":"10.1109\/CVPRW50498.2020.00359"},{"key":"7_CR9","doi-asserted-by":"crossref","unstructured":"Deng, J., Dong, W., Socher, R., Li, L.J., Li, K., Fei-Fei, L.: ImageNet: a large-scale hierarchical image database. In: 2009 IEEE Conference on Computer Vision and Pattern Recognition, pp. 248\u2013255. IEEE (2009)","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"7_CR10","doi-asserted-by":"crossref","unstructured":"Fang, C., Xu, Y., Rockmore, D.N.: Unbiased metric learning: on the utilization of multiple datasets and web images for softening bias. In: Proceedings of the IEEE International Conference on Computer Vision. pp. 1657\u20131664 (2013)","DOI":"10.1109\/ICCV.2013.208"},{"key":"7_CR11","unstructured":"Foret, P., Kleiner, A., Mobahi, H., Neyshabur, B.: Sharpness-aware minimization for efficiently improving generalization. arXiv preprint arXiv:2010.01412 (2020)"},{"issue":"1","key":"7_CR12","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1162\/neco.1992.4.1.1","volume":"4","author":"S Geman","year":"1992","unstructured":"Geman, S., Bienenstock, E., Doursat, R.: Neural networks and the bias\/variance dilemma. Neural Comput. 4(1), 1\u201358 (1992)","journal-title":"Neural Comput."},{"key":"7_CR13","unstructured":"Gulrajani, I., Lopez-Paz, D.: In search of lost domain generalization. In: International Conference on Learning Representations (2020)"},{"key":"7_CR14","doi-asserted-by":"crossref","unstructured":"Guo, J., Qi, L., Shi, Y.: Domaindrop: Suppressing domain-sensitive channels for domain generalization. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 19114\u201319124 (2023)","DOI":"10.1109\/ICCV51070.2023.01751"},{"issue":"7","key":"7_CR15","doi-asserted-by":"publisher","first-page":"1873","DOI":"10.1364\/JOSAA.24.001873","volume":"24","author":"BC Hansen","year":"2007","unstructured":"Hansen, B.C., Hess, R.F.: Structural sparseness and spatial phase alignment in natural scenes. JOSA A 24(7), 1873\u20131885 (2007)","journal-title":"JOSA A"},{"key":"7_CR16","doi-asserted-by":"crossref","unstructured":"He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 770\u2013778 (2016)","DOI":"10.1109\/CVPR.2016.90"},{"key":"7_CR17","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":"7_CR18","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"124","DOI":"10.1007\/978-3-030-58536-5_8","volume-title":"Computer Vision \u2013 ECCV 2020","author":"Z Huang","year":"2020","unstructured":"Huang, Z., Wang, H., Xing, E.P., Huang, D.: Self-challenging improves cross-domain generalization. In: Vedaldi, A., Bischof, H., Brox, T., Frahm, J.-M. (eds.) ECCV 2020. LNCS, vol. 12347, pp. 124\u2013140. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-58536-5_8"},{"key":"7_CR19","doi-asserted-by":"crossref","unstructured":"Kim, D., Yoo, Y., Park, S., Kim, J., Lee, J.: SelfReg: self-supervised contrastive regularization for domain generalization. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 9619\u20139628 (2021)","DOI":"10.1109\/ICCV48922.2021.00948"},{"key":"7_CR20","doi-asserted-by":"crossref","unstructured":"Lee, S., Bae, J., Kim, H.Y.: Decompose, adjust, compose: effective normalization by playing with frequency for domain generalization. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 11776\u201311785 (2023)","DOI":"10.1109\/CVPR52729.2023.01133"},{"key":"7_CR21","doi-asserted-by":"crossref","unstructured":"Li, C., Zhang, D., Huang, W., Zhang, J.: Cross contrasting feature perturbation for domain generalization. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 1327\u20131337 (2023)","DOI":"10.1109\/ICCV51070.2023.00128"},{"key":"7_CR22","doi-asserted-by":"crossref","unstructured":"Li, D., Yang, Y., Song, Y.Z., Hospedales, T.M.: Deeper, broader and artier domain generalization. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 5542\u20135550 (2017)","DOI":"10.1109\/ICCV.2017.591"},{"key":"7_CR23","doi-asserted-by":"crossref","unstructured":"Li, H., Pan, S.J., Wang, S., Kot, A.C.: Domain generalization with adversarial feature learning. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 5400\u20135409 (2018)","DOI":"10.1109\/CVPR.2018.00566"},{"key":"7_CR24","doi-asserted-by":"crossref","unstructured":"Li, P., Li, D., Li, W., Gong, S., Fu, Y., Hospedales, T.M.: A simple feature augmentation for domain generalization. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 8886\u20138895 (2021)","DOI":"10.1109\/ICCV48922.2021.00876"},{"key":"7_CR25","doi-asserted-by":"crossref","unstructured":"Lv, F., Liang, J., Li, S., Zang, B., Liu, C.H., Wang, Z., Liu, D.: Causality inspired representation learning for domain generalization. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 8046\u20138056 (2022)","DOI":"10.1109\/CVPR52688.2022.00788"},{"key":"7_CR26","unstructured":"Mahajan, D., Tople, S., Sharma, A.: Domain generalization using causal matching. In: International Conference on Machine Learning, pp. 7313\u20137324. PMLR (2021)"},{"key":"7_CR27","series-title":"LNCS","doi-asserted-by":"publisher","first-page":"37","DOI":"10.1007\/978-3-030-58536-5_8","volume-title":"European Conference on Computer Vision","author":"S Min","year":"2022","unstructured":"Min, S., Park, N., Kim, S., Park, S., Kim, J.: Grounding visual representations with texts for domain generalization. In: Vedaldi, A., Bischof, H., Brox, T., Frahm, J.M. (eds.) European Conference on Computer Vision. LNCS, vol. 12347, pp. 37\u201353. Springer, Cham (2022). https:\/\/doi.org\/10.1007\/978-3-030-58536-5_8"},{"key":"7_CR28","unstructured":"Muandet, K., Balduzzi, D., Sch\u00f6lkopf, B.: Domain generalization via invariant feature representation. In: International Conference on Machine Learning, pp. 10\u201318. PMLR (2013)"},{"key":"7_CR29","doi-asserted-by":"crossref","unstructured":"Oppenheim, A., Lim, J., Kopec, G., Pohlig, S.: Phase in speech and pictures. In: ICASSP\u201979. IEEE International Conference on Acoustics, Speech, and Signal Processing, vol.\u00a04, pp. 632\u2013637. IEEE (1979)","DOI":"10.1109\/ICASSP.1979.1170798"},{"key":"7_CR30","doi-asserted-by":"crossref","unstructured":"Peng, X., Bai, Q., Xia, X., Huang, Z., Saenko, K., Wang, B.: Moment matching for multi-source domain adaptation. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 1406\u20131415 (2019)","DOI":"10.1109\/ICCV.2019.00149"},{"key":"7_CR31","unstructured":"Peng, X., Huang, Z., Sun, X., Saenko, K.: Domain agnostic learning with disentangled representations. In: International Conference on Machine Learning, pp. 5102\u20135112. PMLR (2019)"},{"issue":"3","key":"7_CR32","doi-asserted-by":"publisher","first-page":"337","DOI":"10.1068\/p110337","volume":"11","author":"LN Piotrowski","year":"1982","unstructured":"Piotrowski, L.N., Campbell, F.W.: A demonstration of the visual importance and flexibility of spatial-frequency amplitude and phase. Perception 11(3), 337\u2013346 (1982)","journal-title":"Perception"},{"key":"7_CR33","unstructured":"Piratla, V., Netrapalli, P., Sarawagi, S.: Efficient domain generalization via common-specific low-rank decomposition. In: International Conference on Machine Learning, pp. 7728\u20137738. PMLR (2020)"},{"key":"7_CR34","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"68","DOI":"10.1007\/978-3-030-58542-6_5","volume-title":"Computer Vision \u2013 ECCV 2020","author":"S Seo","year":"2020","unstructured":"Seo, S., Suh, Y., Kim, D., Kim, G., Han, J., Han, B.: Learning to optimize domain specific normalization for domain generalization. In: Vedaldi, A., Bischof, H., Brox, T., Frahm, J.-M. (eds.) ECCV 2020, Part XXII. LNCS, vol. 12367, pp. 68\u201383. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-58542-6_5"},{"key":"7_CR35","unstructured":"Shi, Y., et al.: Gradient matching for domain generalization. arXiv preprint arXiv:2104.09937 (2021)"},{"key":"7_CR36","doi-asserted-by":"crossref","unstructured":"Venkateswara, H., Eusebio, J., Chakraborty, S., Panchanathan, S.: Deep hashing network for unsupervised domain adaptation. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 5018\u20135027 (2017)","DOI":"10.1109\/CVPR.2017.572"},{"key":"7_CR37","doi-asserted-by":"crossref","unstructured":"Wang, G., Han, H., Shan, S., Chen, X.: Cross-domain face presentation attack detection via multi-domain disentangled representation learning. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 6678\u20136687 (2020)","DOI":"10.1109\/CVPR42600.2020.00671"},{"key":"7_CR38","doi-asserted-by":"crossref","unstructured":"Wang, P., Zhang, Z., Lei, Z., Zhang, L.: Sharpness-aware gradient matching for domain generalization. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 3769\u20133778 (2023)","DOI":"10.1109\/CVPR52729.2023.00367"},{"issue":"8","key":"7_CR39","doi-asserted-by":"publisher","first-page":"5495","DOI":"10.1109\/TCSVT.2022.3152615","volume":"32","author":"Y Wang","year":"2022","unstructured":"Wang, Y., Qi, L., Shi, Y., Gao, Y.: Feature-based style randomization for domain generalization. IEEE Trans. Circuits Syst. Video Technol. 32(8), 5495\u20135509 (2022)","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"7_CR40","doi-asserted-by":"crossref","unstructured":"Xu, M., Zhang, J., Ni, B., Li, T., Wang, C., Tian, Q., Zhang, W.: Adversarial domain adaptation with domain mixup. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol.\u00a034, pp. 6502\u20136509 (2020)","DOI":"10.1609\/aaai.v34i04.6123"},{"key":"7_CR41","doi-asserted-by":"crossref","unstructured":"Xu, Q., Zhang, R., Zhang, Y., Wang, Y., Tian, Q.: A Fourier-based framework for domain generalization. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 14383\u201314392 (2021)","DOI":"10.1109\/CVPR46437.2021.01415"},{"key":"7_CR42","first-page":"19448","volume":"34","author":"FE Yang","year":"2021","unstructured":"Yang, F.E., Cheng, Y.C., Shiau, Z.Y., Wang, Y.C.F.: Adversarial teacher-student representation learning for domain generalization. Adv. Neural. Inf. Process. Syst. 34, 19448\u201319460 (2021)","journal-title":"Adv. Neural. Inf. Process. Syst."},{"key":"7_CR43","unstructured":"Yang, Z., Yu, Y., You, C., Steinhardt, J., Ma, Y.: Rethinking bias-variance trade-off for generalization of neural networks. In: International Conference on Machine Learning, pp. 10767\u201310777. PMLR (2020)"},{"key":"7_CR44","series-title":"LNCS","doi-asserted-by":"publisher","first-page":"161","DOI":"10.1007\/978-3-031-19812-0_10","volume-title":"ECCV 2022","author":"J Zhang","year":"2022","unstructured":"Zhang, J., Qi, L., Shi, Y., Gao, Y.: MVDG: a unified multi-view framework for domain generalization. In: Avidan, S., Brostow, G., Ciss\u00e9, M., Farinella, G.M., Hassner, T. (eds.) ECCV 2022. LNCS, vol. 13687, pp. 161\u2013177. Springer, Cham (2022). https:\/\/doi.org\/10.1007\/978-3-031-19812-0_10"},{"key":"7_CR45","doi-asserted-by":"crossref","unstructured":"Zhang, X., Xu, R., Yu, H., Dong, Y., Tian, P., Cui, P.: Flatness-aware minimization for domain generalization. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 5189\u20135202 (2023)","DOI":"10.1109\/ICCV51070.2023.00479"},{"key":"7_CR46","first-page":"16096","volume":"33","author":"S Zhao","year":"2020","unstructured":"Zhao, S., Gong, M., Liu, T., Fu, H., Tao, D.: Domain generalization via entropy regularization. Adv. Neural. Inf. Process. Syst. 33, 16096\u201316107 (2020)","journal-title":"Adv. Neural. Inf. Process. Syst."},{"key":"7_CR47","doi-asserted-by":"crossref","unstructured":"Zhou, K., Yang, Y., Hospedales, T., Xiang, T.: Deep domain-adversarial image generation for domain generalisation. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol.\u00a034, pp. 13025\u201313032 (2020)","DOI":"10.1609\/aaai.v34i07.7003"},{"key":"7_CR48","doi-asserted-by":"crossref","unstructured":"Zhu, W., Lu, L., Xiao, J., Han, M., Luo, J., Harrison, A.P.: Localized adversarial domain generalization. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 7108\u20137118 (2022)","DOI":"10.1109\/CVPR52688.2022.00697"}],"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\/978-3-031-72764-1_7","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,24]],"date-time":"2024-10-24T14:05:15Z","timestamp":1729778715000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-72764-1_7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,10,25]]},"ISBN":["9783031727634","9783031727641"],"references-count":48,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-72764-1_7","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,10,25]]},"assertion":[{"value":"25 October 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"}}]}}