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However, when applied to image full\u2010body visual privacy protection in open\u2010world scenarios, where abnormal visual privacy data may exist in the training data, issues such as mode collapse and instability in GANs can be severely exacerbated. This leads to a significant reduction in both image quality and utility preservation. In this paper, we propose an end\u2010to\u2010end, contrastive GANs\u2010based framework, FBPPGAN, for image full\u2010body visual privacy protection, specifically designed to address these challenges. First, we introduce the architecture of FBPPGAN, which is tailored for full\u2010body visual privacy protection. Second, we propose a novel adversarial loss function aimed at mitigating mode collapse and instability, particularly in the presence of abnormal images in open\u2010world environments. We also design a content mapping network and a content loss function based on contrastive learning to address the issue of insufficient color gamut in generated images. Furthermore, a stylized loss function is introduced to more accurately measure the difference between the generated and target domains. Experimental results across four public datasets demonstrate that FBPPGAN effectively overcomes mode collapse and instability, delivering superior image quality and utility preservation. Compared to the existing state\u2010of\u2010the\u2010art methods, FBPPGAN outperforms in terms of convergence, stability, computational complexity, processing speed, and effectiveness. To the best of our knowledge, this is the first GAN\u2010based framework for image full\u2010body visual privacy protection in open\u2010world\u00a0scenarios.<\/jats:p>","DOI":"10.1049\/cmu2.70128","type":"journal-article","created":{"date-parts":[[2026,1,19]],"date-time":"2026-01-19T10:36:57Z","timestamp":1768819017000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A Contrastive GAN\u2010Based Framework for Full\u2010Body Visual Privacy Protection in Open World Scenarios"],"prefix":"10.1049","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7903-6414","authenticated-orcid":false,"given":"Haolong","family":"Fu","sequence":"first","affiliation":[{"name":"Hunan Vanguard Group Corporation Limited Changsha China"}]},{"given":"Xuan","family":"He","sequence":"additional","affiliation":[{"name":"Hunan Vanguard Group Corporation Limited Changsha China"}]}],"member":"265","published-online":{"date-parts":[[2026,1,19]]},"reference":[{"issue":"5","key":"e_1_2_11_2_1","doi-asserted-by":"crossref","first-page":"14715","DOI":"10.1007\/s11042-023-15775-2","article-title":"A Review on Visual Privacy Preservation Techniques for Active and Assisted Living","volume":"83","author":"Ravi S.","year":"2024","journal-title":"Multimedia Tools and Applications"},{"key":"e_1_2_11_3_1","doi-asserted-by":"publisher","DOI":"10.1145\/3708501"},{"key":"e_1_2_11_4_1","unstructured":"Organisation for Economic Co\u2010Operation and Development \u201cThe OECD Privacy Framework \u201d2013 accessed May 27 2020 https:\/\/www.afapdp.org\/wp\u2010content\/uploads\/2018\/06\/oecd_privacy_framework.pdf."},{"key":"e_1_2_11_5_1","unstructured":"International Organization for Standardization Security Techniques: Extension to ISO\/IEC 27001 and ISO\/IEC 27002 for Privacy Information Management\u2013Requirements and Guidelines Standard ISO\/IEC 27701 (2019)."},{"key":"e_1_2_11_6_1","unstructured":"International Organization for Standardization Privacy Enhancing Data De\u2010Identification Terminology and Classification of Techniques Standard ISO\/IEC 20889 (2018)."},{"key":"e_1_2_11_7_1","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1145\/2087756.2087759","volume-title":"VRCAI '11: Proceedings of the 10th International Conference on Virtual Reality Continuum and Its Applications in Industry","author":"Hauswiesner S.","year":"2011"},{"issue":"4","key":"e_1_2_11_8_1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3592611","article-title":"E\u2010TPE: Efficient Thumbnail\u2010Preserving Encryption for Privacy Protection in Visual Sensor Networks","volume":"20","author":"Zhao R.","year":"2024","journal-title":"ACM Transactions on Sensor Networks"},{"key":"e_1_2_11_9_1","first-page":"12120","volume-title":"IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","author":"Lopez J.","year":"2024"},{"key":"e_1_2_11_10_1","doi-asserted-by":"crossref","unstructured":"Z.Cai Z.Gao B.Planche et\u00a0al. \u201cDisguise Without Disruption: Utility\u2010Preserving Face De\u2010Identification \u201d inAAAI'24\/IAAI'24\/EAAI'24: Proceedings of the Thirty\u2010Eighth AAAI Conference on Artificial Intelligence and Thirty\u2010Sixth Conference on Innovative Applications of Artificial Intelligence and Fourteenth Symposium on Educational Advances in Artificial Intelligence Vol.38(ACM 2024) 918\u2013926.","DOI":"10.1609\/aaai.v38i2.27851"},{"key":"e_1_2_11_11_1","first-page":"1","volume-title":"IEEE International Conference and Workshops on Automatic Face and Gesture Recognition (FG)","author":"Sun Z.","year":"2015"},{"issue":"1","key":"e_1_2_11_12_1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/1143518.1143519","article-title":"Blur Filtration Fails to Preserve Privacy for Home\u2010Based Video Conferencing","volume":"13","author":"Neustaedter C.","year":"2006","journal-title":"ACM Transactions on Computer\u2010Human Interaction"},{"key":"e_1_2_11_13_1","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2023.120960","article-title":"BRPPNet: Balanced Privacy Protection Network for Referring Personal Image Privacy Protection","volume":"233","author":"Lin J.","year":"2023","journal-title":"Expert Systems With Applications"},{"key":"e_1_2_11_14_1","doi-asserted-by":"publisher","DOI":"10.3390\/app15031261"},{"key":"e_1_2_11_15_1","doi-asserted-by":"crossref","unstructured":"M.Sankari P.Ranjana andD. 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