{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,4]],"date-time":"2026-06-04T15:21:28Z","timestamp":1780586488734,"version":"3.54.1"},"publisher-location":"Singapore","reference-count":31,"publisher":"Springer Nature Singapore","isbn-type":[{"value":"9789819557363","type":"print"},{"value":"9789819557370","type":"electronic"}],"license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"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":[[2026]]},"DOI":"10.1007\/978-981-95-5737-0_34","type":"book-chapter","created":{"date-parts":[[2026,1,2]],"date-time":"2026-01-02T03:11:28Z","timestamp":1767323488000},"page":"482-496","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["AnyView VTON: Consistent 3D Virtual Try-On with\u00a0View-Conditioned Diffusion Model"],"prefix":"10.1007","author":[{"given":"Feng","family":"Zhang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Maochun","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhenming","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hao","family":"Feng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Biao","family":"Guo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Junyan","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yao","family":"Lu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ming","family":"Jiang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,1,2]]},"reference":[{"key":"34_CR1","doi-asserted-by":"crossref","unstructured":"Choi, S., Park, S., Lee, M., Choo, J.: VITON-HD: high-resolution virtual try-on via misalignment-aware normalization. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 14131\u201314140 (2021)","DOI":"10.1109\/CVPR46437.2021.01391"},{"key":"34_CR2","doi-asserted-by":"crossref","unstructured":"Lee, S., Gu, G., Park, S., Choi, S., Choo, J.: High-resolution virtual try-on with misalignment and occlusion-handled conditions. In: European Conference on Computer Vision, pp. 204\u2013219. Springer (2022)","DOI":"10.1007\/978-3-031-19790-1_13"},{"key":"34_CR3","unstructured":"Goodfellow, I.J., et al.: Generative adversarial nets. In: Advances in Neural Information Processing Systems, vol. 27 (2014)"},{"key":"34_CR4","unstructured":"Dhariwal, P., Nichol, A.: Diffusion models beat GANs on image synthesis. In: Advances in Neural Information Processing Systems, vol. 34, pp. 8780\u20138794 (2021)"},{"key":"34_CR5","doi-asserted-by":"crossref","unstructured":"Zhu, L., et al.: TryOnDiffusion: a tale of two UNets. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 4606\u20134615 (2023)","DOI":"10.1109\/CVPR52729.2023.00447"},{"key":"34_CR6","doi-asserted-by":"crossref","unstructured":"Xu, Y., Gu, T., Chen, W., Chen, A.: OOTDiffusion: outfitting fusion based latent diffusion for controllable virtual try-on. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol.\u00a039, pp. 8996\u20139004 (2025)","DOI":"10.1609\/aaai.v39i9.32973"},{"key":"34_CR7","doi-asserted-by":"crossref","unstructured":"Choi, Y., Kwak, S., Lee, K., Choi, H., Shin, J.: Improving diffusion models for authentic virtual try-on in the wild. In: European Conference on Computer Vision, pp. 206\u2013235. Springer (2024)","DOI":"10.1007\/978-3-031-73016-0_13"},{"key":"34_CR8","unstructured":"Chen, H., Huang, Y., Huang, H., Ge, X., Shao, D.: GaussianVTON: 3D human virtual try-on via multi-stage gaussian splatting editing with image prompting. arXiv preprint arXiv:2405.07472 (2024)"},{"key":"34_CR9","unstructured":"Cao, Y., Hadi, M., Pan, L., Liu, Z.: GS-VTON: controllable 3D virtual try-on with Gaussian splatting. arXiv preprint arXiv:2410.05259 (2024)"},{"key":"34_CR10","doi-asserted-by":"crossref","unstructured":"Kerbl, B., Kopanas, G., Leimk\u00fchler, T., Drettakis, G.: 3D Gaussian splatting for real-time radiance field rendering. ACM Trans. Graph. 42(4), 1\u201314, 139 (2023)","DOI":"10.1145\/3592433"},{"key":"34_CR11","doi-asserted-by":"crossref","unstructured":"Xie, Z., Dong, H., Gao, Y., Ma, Z., Liang, X.: DreamVTON: customizing 3D virtual try-on with personalized diffusion models. In: Proceedings of the 32nd ACM International Conference on Multimedia, pp. 10784\u201310793 (2024)","DOI":"10.1145\/3664647.3681391"},{"key":"34_CR12","doi-asserted-by":"crossref","unstructured":"He, Z., et al.: VTON 360: high-fidelity virtual try-on from any viewing direction. In: Proceedings of the Computer Vision and Pattern Recognition Conference, pp. 26388\u201326398 (2025)","DOI":"10.1109\/CVPR52734.2025.02457"},{"key":"34_CR13","doi-asserted-by":"crossref","unstructured":"Yu, T., Zheng, Z., Guo, K., Liu, P., Dai, Q., Liu, Y.: Function4D: real-time human volumetric capture from very sparse consumer RGBD sensors. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 5746\u20135756 (2021)","DOI":"10.1109\/CVPR46437.2021.00569"},{"key":"34_CR14","unstructured":"Ho, J., Jain, A., Abbeel, P.: Denoising diffusion probabilistic models. In: Advances in Neural Information Processing Systems, vol. 33, pp. 6840\u20136851 (2020)"},{"key":"34_CR15","unstructured":"Song, Y., Sohl-Dickstein, J., Kingma, D.P., Kumar, A., Ermon, S., Poole, B.: Score-based generative modeling through stochastic differential equations. In: International Conference on Learning Representations (2021). https:\/\/openreview.net\/forum?id=PxTIG12RRHS"},{"key":"34_CR16","doi-asserted-by":"crossref","unstructured":"Hu, L.: Animate anyone: consistent and controllable image-to-video synthesis for character animation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 8153\u20138163 (2024)","DOI":"10.1109\/CVPR52733.2024.00779"},{"key":"34_CR17","doi-asserted-by":"crossref","unstructured":"Wang, H., Zhang, Z., Di, D., Zhang, S., Zuo, W.: MV-VTON: multi-view virtual try-on with diffusion models. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol.\u00a039, pp. 7682\u20137690 (2025)","DOI":"10.1609\/aaai.v39i7.32827"},{"key":"34_CR18","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"698","DOI":"10.1007\/978-3-030-01225-0_41","volume-title":"Computer Vision \u2013 ECCV 2018","author":"Z L\u00e4hner","year":"2018","unstructured":"L\u00e4hner, Z., Cremers, D., Tung, T.: DeepWrinkles: accurate and realistic clothing modeling. In: Ferrari, V., Hebert, M., Sminchisescu, C., Weiss, Y. (eds.) ECCV 2018. LNCS, vol. 11208, pp. 698\u2013715. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-030-01225-0_41"},{"key":"34_CR19","doi-asserted-by":"publisher","unstructured":"Pons-Moll, G., Pujades, S., Hu, S., Black, M.J.: ClothCap: seamless 4D clothing capture and retargeting. ACM Trans. Graph. 36(4) (2017). https:\/\/doi.org\/10.1145\/3072959.3073711","DOI":"10.1145\/3072959.3073711"},{"key":"34_CR20","doi-asserted-by":"crossref","unstructured":"Bhatnagar, B.L., Tiwari, G., Theobalt, C., Pons-Moll, G.: Multi-garment net: learning to dress 3D people from images. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 5420\u20135430 (2019)","DOI":"10.1109\/ICCV.2019.00552"},{"key":"34_CR21","doi-asserted-by":"crossref","unstructured":"Mir, A., Alldieck, T., Pons-Moll, G.: Learning to transfer texture from clothing images to 3D humans. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 7023\u20137034 (2020)","DOI":"10.1109\/CVPR42600.2020.00705"},{"key":"34_CR22","doi-asserted-by":"publisher","unstructured":"Loper, M., Mahmood, N., Romero, J., Pons-Moll, G., Black, M.J.: SMPL: A Skinned Multi-Person Linear Model, 1 edn. Association for Computing Machinery, New York, NY, USA (2023). https:\/\/doi.org\/10.1145\/3596711.3596800","DOI":"10.1145\/3596711.3596800"},{"issue":"2","key":"34_CR23","first-page":"3","volume":"1","author":"EJ Hu","year":"2022","unstructured":"Hu, E.J., et al.: LoRA: low-rank adaptation of large language models. ICLR 1(2), 3 (2022)","journal-title":"ICLR"},{"key":"34_CR24","doi-asserted-by":"crossref","unstructured":"Rombach, R., Blattmann, A., Lorenz, D., Esser, P., Ommer, B.: High-resolution image synthesis with latent diffusion models. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 10684\u201310695 (2022)","DOI":"10.1109\/CVPR52688.2022.01042"},{"key":"34_CR25","unstructured":"Kingma, D.P., Welling, M., et\u00a0al.: Auto-encoding variational bayes. arXiv preprint arXiv:1312.6114 (2013)"},{"key":"34_CR26","doi-asserted-by":"crossref","unstructured":"Yang, B., et al.: Paint by example: exemplar-based image editing with diffusion models. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 18381\u201318391 (2023)","DOI":"10.1109\/CVPR52729.2023.01763"},{"key":"34_CR27","unstructured":"Radford, A., et\u00a0al.: Learning transferable visual models from natural language supervision. In: International Conference on Machine Learning, pp. 8748\u20138763. PMLR (2021)"},{"issue":"1","key":"34_CR28","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."},{"key":"34_CR29","doi-asserted-by":"crossref","unstructured":"Wu, J., et al.: GaussCtrl: multi-view consistent text-driven 3D Gaussian splatting editing. In: ECCV (2024)","DOI":"10.1007\/978-3-031-72630-9_4"},{"key":"34_CR30","unstructured":"Oquab, M., et\u00a0al.: DINOv2: learning robust visual features without supervision. arXiv preprint arXiv:2304.07193 (2023)"},{"key":"34_CR31","doi-asserted-by":"crossref","unstructured":"Haque, A., Tancik, M., Efros, A.A., Holynski, A., Kanazawa, A.: Instruct-NeRF2neRF: editing 3D scenes with instructions. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 19740\u201319750 (2023)","DOI":"10.1109\/ICCV51070.2023.01808"}],"container-title":["Lecture Notes in Computer Science","Pattern Recognition and Computer Vision"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-95-5737-0_34","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,2]],"date-time":"2026-01-02T03:11:30Z","timestamp":1767323490000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-95-5737-0_34"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026]]},"ISBN":["9789819557363","9789819557370"],"references-count":31,"URL":"https:\/\/doi.org\/10.1007\/978-981-95-5737-0_34","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026]]},"assertion":[{"value":"2 January 2026","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"PRCV","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Chinese Conference on Pattern Recognition and Computer Vision  (PRCV)","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Shanghai","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2025","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15 October 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18 October 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ccprcv2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/2025.prcv.cn\/index.asp","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}