{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,31]],"date-time":"2025-03-31T05:26:31Z","timestamp":1743398791356,"version":"3.33.0"},"reference-count":62,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2024,4,2]],"date-time":"2024-04-02T00:00:00Z","timestamp":1712016000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,4,2]],"date-time":"2024-04-02T00:00:00Z","timestamp":1712016000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["62206083","62201200"],"award-info":[{"award-number":["62206083","62201200"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Vis Comput"],"published-print":{"date-parts":[[2025,1]]},"DOI":"10.1007\/s00371-024-03331-4","type":"journal-article","created":{"date-parts":[[2024,4,2]],"date-time":"2024-04-02T05:02:12Z","timestamp":1712034132000},"page":"383-397","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Unpaired semantic neural person image synthesis"],"prefix":"10.1007","volume":"41","author":[{"given":"Yixiu","family":"Liu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tao","family":"Jiang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Pengju","family":"Si","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shangdong","family":"Zhu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chenggang","family":"Yan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shuai","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Haibing","family":"Yin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,4,2]]},"reference":[{"key":"3331_CR1","doi-asserted-by":"publisher","first-page":"50","DOI":"10.1109\/TMM.2021.3120873","volume":"25","author":"X Lin","year":"2023","unstructured":"Lin, X., Sun, S., Huang, W., Sheng, B., Li, P., Feng, D.D.: Eapt: efficient attention pyramid transformer for image processing. IEEE Trans. Multimed. 25, 50\u201361 (2023)","journal-title":"IEEE Trans. Multimed."},{"key":"3331_CR2","doi-asserted-by":"publisher","first-page":"2226","DOI":"10.1109\/TMM.2022.3144890","volume":"25","author":"N Jiang","year":"2023","unstructured":"Jiang, N., Sheng, B., Li, P., Lee, T.-Y.: Photohelper: portrait photographing guidance via deep feature retrieval and fusion. IEEE Trans. Multimed. 25, 2226\u20132238 (2023)","journal-title":"IEEE Trans. Multimed."},{"issue":"7","key":"3331_CR3","doi-asserted-by":"publisher","first-page":"6662","DOI":"10.1109\/TCYB.2021.3079311","volume":"52","author":"B Sheng","year":"2022","unstructured":"Sheng, B., Li, P., Ali, R., Chen, C.L.P.: Improving video temporal consistency via broad learning system. IEEE Trans. Cybern. 52(7), 6662\u20136675 (2022)","journal-title":"IEEE Trans. Cybern."},{"issue":"8","key":"3331_CR4","doi-asserted-by":"publisher","first-page":"4499","DOI":"10.1109\/TNNLS.2021.3116209","volume":"34","author":"Z Xie","year":"2023","unstructured":"Xie, Z., Zhang, W., Sheng, B., Li, P., Chen, C.L.P.: Bagfn: broad attentive graph fusion network for high-order feature interactions. IEEE Trans. Neural Netw. Learn. Syst. 34(8), 4499\u20134513 (2023)","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"3331_CR5","doi-asserted-by":"publisher","DOI":"10.1002\/cav.2047","volume":"34","author":"R Li","year":"2023","unstructured":"Li, R., Oji, R., Fujishiro, I.: Controllable automatic generation of non-player characters in 3d anime style. Comput. Anim. Virtual Worlds 34, e2047 (2023)","journal-title":"Comput. Anim. Virtual Worlds"},{"issue":"3\u20134","key":"3331_CR6","doi-asserted-by":"publisher","DOI":"10.1002\/cav.2187","volume":"34","author":"L Sun","year":"2023","unstructured":"Sun, L., Tang, T., Qu, Y., Qin, W.: Bidirectional temporal feature for 3d human pose and shape estimation from a video. Comput. Anim. Virtual Worlds 34(3\u20134), e2187 (2023)","journal-title":"Comput. Anim. Virtual Worlds"},{"issue":"3\u20134","key":"3331_CR7","doi-asserted-by":"publisher","DOI":"10.1002\/cav.2092","volume":"33","author":"W Qin","year":"2022","unstructured":"Qin, W., Tao, R., Sun, L., Dong, K.: Muscle-driven virtual human motion generation approach based on deep reinforcement learning. Comput. Anim. Virtual Worlds 33(3\u20134), e2092 (2022)","journal-title":"Comput. Anim. Virtual Worlds"},{"key":"3331_CR8","doi-asserted-by":"publisher","DOI":"10.1002\/cav.2169","volume":"34","author":"H Trivedi","year":"2023","unstructured":"Trivedi, H., Mousas, C.: Human-virtual crowd interaction: towards understanding the effects of crowd avoidance proximity in an immersive virtual environment. Comput. Anim. Virtual Worlds 34, e2169 (2023)","journal-title":"Comput. Anim. Virtual Worlds"},{"key":"3331_CR9","doi-asserted-by":"crossref","unstructured":"Zhu, Z., Huang, T., Shi, B., Yu, M., Wang, B., Bai, X.: Progressive pose attention transfer for person image generation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 2347\u20132356 (2019)","DOI":"10.1109\/CVPR.2019.00245"},{"key":"3331_CR10","doi-asserted-by":"crossref","unstructured":"Tang, H., Bai, S., Zhang, L., Torr, P.H., Sebe, N.: Xinggan for person image generation. In: Computer Vision-ECCV: 16th European Conference, Glasgow, UK, August 23\u201328, 2020, Proceedings, Part XXV 16, pp. 717\u2013734. Springer (2020)","DOI":"10.1007\/978-3-030-58595-2_43"},{"key":"3331_CR11","doi-asserted-by":"crossref","unstructured":"Zhang, P., Yang, L., Lai, J.-H., Xie, X.: Exploring dual-task correlation for pose guided person image generation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 7713\u20137722 (2022)","DOI":"10.1109\/CVPR52688.2022.00756"},{"key":"3331_CR12","doi-asserted-by":"crossref","unstructured":"Zhang, J., Li, K., Lai, Y.-K., Yang, J.: Pise: Person image synthesis and editing with decoupled GAN. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 7982\u20137990 (2021)","DOI":"10.1109\/CVPR46437.2021.00789"},{"key":"3331_CR13","doi-asserted-by":"crossref","unstructured":"Lv, Z., Li, X., Li, X., Li, F., Lin, T., He, D., Zuo, W.: Learning semantic person image generation by region-adaptive normalization. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 10806\u201310815 (2021)","DOI":"10.1109\/CVPR46437.2021.01066"},{"key":"3331_CR14","doi-asserted-by":"crossref","unstructured":"Men, Y., Mao, Y., Jiang, Y., Ma, W.-Y., Lian, Z.: Controllable person image synthesis with attribute-decomposed GAN. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 5084\u20135093 (2020)","DOI":"10.1109\/CVPR42600.2020.00513"},{"key":"3331_CR15","doi-asserted-by":"crossref","unstructured":"Esser, P., Sutter, E., Ommer, B.: A variational u-net for conditional appearance and shape generation. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 8857\u20138866 (2018)","DOI":"10.1109\/CVPR.2018.00923"},{"key":"3331_CR16","doi-asserted-by":"crossref","unstructured":"Ma, L., Sun, Q., Georgoulis, S., Van\u00a0Gool, L., Schiele, B., Fritz, M.: Disentangled person image generation. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 99\u2013108 (2018)","DOI":"10.1109\/CVPR.2018.00018"},{"key":"3331_CR17","doi-asserted-by":"crossref","unstructured":"Song, S., Zhang, W., Liu, J., Mei, T.: Unsupervised person image generation with semantic parsing transformation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 2357\u20132366 (2019)","DOI":"10.1109\/CVPR.2019.00246"},{"key":"3331_CR18","doi-asserted-by":"crossref","unstructured":"Wang, Z., Qi, X., Yuan, K., Sun, M.: Self-supervised correlation mining network for person image generation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 7703\u20137712 (2022)","DOI":"10.1109\/CVPR52688.2022.00755"},{"key":"3331_CR19","doi-asserted-by":"crossref","unstructured":"Ma, T., Peng, B., Wang, W., Dong, J.: Must-gan: Multi-level statistics transfer for self-driven person image generation,\u201d in Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 13\u00a0622\u201313\u00a0631 (2021)","DOI":"10.1109\/CVPR46437.2021.01341"},{"key":"3331_CR20","doi-asserted-by":"crossref","unstructured":"Pumarola, A., Agudo, A., Sanfeliu, A., Moreno-Noguer, F.: \u201cUnsupervised person image synthesis in arbitrary poses,\u201d in Proceedings of the IEEE conference on computer vision and pattern recognition, 8620\u20138628 (2018)","DOI":"10.1109\/CVPR.2018.00899"},{"key":"3331_CR21","doi-asserted-by":"crossref","unstructured":"Li, N., Shih, K.\u00a0J., Plummer, B.\u00a0A.: \u201cCollecting the puzzle pieces: Disentangled self-driven human pose transfer by permuting textures,\u201d arXiv preprintarXiv:2210.01887, (2022)","DOI":"10.1109\/ICCV51070.2023.00655"},{"key":"3331_CR22","doi-asserted-by":"crossref","unstructured":"Isola, P., Zhu, J.-Y., Zhou, T., Efros, A.\u00a0A.: \u201cImage-to-image translation with conditional adversarial networks,\u201d in Proceedings of the IEEE conference on computer vision and pattern recognition, 1125\u20131134 (2017)","DOI":"10.1109\/CVPR.2017.632"},{"key":"3331_CR23","doi-asserted-by":"crossref","unstructured":"Park, T., Liu, M.-Y., Wang, T.-C., Zhu, J.-Y.: \u201cSemantic image synthesis with spatially-adaptive normalization,\u201d in Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, 2337\u20132346 (2019)","DOI":"10.1109\/CVPR.2019.00244"},{"key":"3331_CR24","unstructured":"Liu, X., Yin, G., Shao, J., Wang, X. et\u00a0al., \u201cLearning to predict layout-to-image conditional convolutions for semantic image synthesis,\u201d Advances in Neural Information Processing Systems, vol.\u00a032, (2019)"},{"key":"3331_CR25","unstructured":"Wang, Y., Qi, L., Chen, Y.-C., Zhang, X., Jia, J.: \u201cImage synthesis via semantic composition,\u201d in Proceedings of the IEEE\/CVF International Conference on Computer Vision, 13\u00a0749\u201313\u00a0758 (2021)"},{"key":"3331_CR26","doi-asserted-by":"crossref","unstructured":"Zhu, P., Abdal, R., Qin, Y., Wonka, P.: \u201cSean: Image synthesis with semantic region-adaptive normalization,\u201d in Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 5104\u20135113 (2020)","DOI":"10.1109\/CVPR42600.2020.00515"},{"issue":"1","key":"3331_CR27","first-page":"1","volume":"41","author":"A Chen","year":"2022","unstructured":"Chen, A., Liu, R., Xie, L., Chen, Z., Su, H., Yu, J.: Sofgan: a portrait image generator with dynamic styling. ACM Trans. Graph. (TOG) 41(1), 1\u201326 (2022)","journal-title":"ACM Trans. Graph. (TOG)"},{"issue":"11","key":"3331_CR28","doi-asserted-by":"publisher","first-page":"139","DOI":"10.1145\/3422622","volume":"63","author":"I Goodfellow","year":"2020","unstructured":"Goodfellow, I., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., Courville, A., Bengio, Y.: Generative adversarial networks. Commun. ACM 63(11), 139\u2013144 (2020)","journal-title":"Commun. ACM"},{"issue":"4","key":"3331_CR29","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3306346.3323035","volume":"38","author":"J Thies","year":"2019","unstructured":"Thies, J., Zollh\u00f6fer, M., Nie\u00dfner, M.: Deferred neural rendering: image synthesis using neural textures. ACM Trans. Graph. (TOG) 38(4), 1\u201312 (2019)","journal-title":"ACM Trans. Graph. (TOG)"},{"key":"3331_CR30","doi-asserted-by":"crossref","unstructured":"Raj, A., Tanke, J., Hays, J., Vo, M., Stoll, C., Lassner, C.: \u201cAnr: Articulated neural rendering for virtual avatars,\u201d in Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 3722\u20133731 (2021)","DOI":"10.1109\/CVPR46437.2021.00372"},{"key":"3331_CR31","doi-asserted-by":"crossref","unstructured":"Grigorev, A., Iskakov, K., Ianina, A., Bashirov, R., Zakharkin, I., Vakhitov, A., Lempitsky, V.: \u201cStylepeople: A generative model of fullbody human avatars,\u201d in Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 5151\u20135160 (2021)","DOI":"10.1109\/CVPR46437.2021.00511"},{"key":"3331_CR32","unstructured":"Su, S.-Y., Yu, F., Zollh\u00f6fer, M., Rhodin, H.: \u201cA-nerf: Articulated neural radiance fields for learning human shape, appearance, and pose,\u201d Advances in Neural Information Processing Systems, 34, 12\u00a0278\u201312\u00a0291, (2021)"},{"key":"3331_CR33","doi-asserted-by":"crossref","unstructured":"Peng, S., Zhang, Y., Xu, Y., Wang, Q., Shuai, Q., Bao, H., Zhou, X.: \u201cNeural body: Implicit neural representations with structured latent codes for novel view synthesis of dynamic humans,\u201d in Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 9054\u20139063 (2021)","DOI":"10.1109\/CVPR46437.2021.00894"},{"key":"3331_CR34","unstructured":"Peng, S., Xu, Z., Dong, J., Wang, Q., Zhang, S., Shuai, Q., Bao, H., Zhou, X.: \u201cAnimatable implicit neural representations for creating realistic avatars from videos,\u201d arXiv preprintarXiv:2203.08133, (2022)"},{"issue":"6","key":"3331_CR35","first-page":"1","volume":"40","author":"L Liu","year":"2021","unstructured":"Liu, L., Habermann, M., Rudnev, V., Sarkar, K., Gu, J., Theobalt, C.: Neural actor: neural free-view synthesis of human actors with pose control. ACM Trans. Graph. (TOG) 40(6), 1\u201316 (2021)","journal-title":"ACM Trans. Graph. (TOG)"},{"issue":"6","key":"3331_CR36","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/2816795.2818013","volume":"34","author":"M Loper","year":"2015","unstructured":"Loper, M., Mahmood, N., Romero, J., Pons-Moll, G., Black, M.J.: Smpl: a skinned multi-person linear model. ACM Trans. Graph. (TOG) 34(6), 1\u201316 (2015)","journal-title":"ACM Trans. Graph. (TOG)"},{"key":"3331_CR37","doi-asserted-by":"crossref","unstructured":"Weng, C.-Y., Curless, B., Srinivasan, P.\u00a0P., Barron, J.\u00a0T., Kemelmacher-Shlizerman, I.: \u201cHumannerf: Free-viewpoint rendering of moving people from monocular video,\u201d in Proceedings of the IEEE\/CVF conference on computer vision and pattern Recognition, 16\u00a0210\u201316\u00a0220 (2022)","DOI":"10.1109\/CVPR52688.2022.01573"},{"key":"3331_CR38","doi-asserted-by":"crossref","unstructured":"Tseng, W.-C., Liao, H.-J., Yen-Chen, L., Sun, M.: \u201cCla-nerf: Category-level articulated neural radiance field,\u201d in 2022 International Conference on Robotics and Automation (ICRA). IEEE, 2022, pp. 8454\u20138460","DOI":"10.1109\/ICRA46639.2022.9812272"},{"key":"3331_CR39","doi-asserted-by":"crossref","unstructured":"Mu, J., Sang, S., Vasconcelos, N., Wang, X.: \u201cActorsnerf: Animatable few-shot human rendering with generalizable nerfs,\u201d arXiv preprintarXiv:2304.14401, (2023)","DOI":"10.1109\/ICCV51070.2023.01686"},{"key":"3331_CR40","doi-asserted-by":"crossref","unstructured":"Liu, S., Zhang, X., Zhang, Z., Zhang, R., Zhu, J.-Y., Russell, B.: \u201cEditing conditional radiance fields,\u201d in Proceedings of the IEEE\/CVF International Conference on Computer Vision, 5773\u20135783 (2021)","DOI":"10.1109\/ICCV48922.2021.00572"},{"key":"3331_CR41","doi-asserted-by":"crossref","unstructured":"Abdal, R., Qin, Y., Wonka, P.: \u201cImage2stylegan: How to embed images into the stylegan latent space?\u201d in Proceedings of the IEEE\/CVF International Conference on Computer Vision, 4432\u20134441 (2019)","DOI":"10.1109\/ICCV.2019.00453"},{"issue":"1","key":"3331_CR42","doi-asserted-by":"publisher","first-page":"99","DOI":"10.1145\/3503250","volume":"65","author":"B Mildenhall","year":"2021","unstructured":"Mildenhall, B., Srinivasan, P.P., Tancik, M., Barron, J.T., Ramamoorthi, R., Ng, R.: Nerf: representing scenes as neural radiance fields for view synthesis. Commun. ACM 65(1), 99\u2013106 (2021)","journal-title":"Commun. ACM"},{"key":"3331_CR43","unstructured":"Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, \u0141.\u00a0Kaiser, A.\u00a0N., Polosukhin, I.: \u201cAttention is all you need,\u201d Advances in neural information processing systems, 30, (2017)"},{"key":"3331_CR44","doi-asserted-by":"crossref","unstructured":"Chan, E.\u00a0R., Monteiro, M., Kellnhofer, P., Wu, J., Wetzstein, G.: \u201cpi-gan: Periodic implicit generative adversarial networks for 3d-aware image synthesis,\u201d in Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 5799\u20135809 (2021)","DOI":"10.1109\/CVPR46437.2021.00574"},{"key":"3331_CR45","doi-asserted-by":"crossref","unstructured":"Perez, E., Strub, F., De\u00a0Vries, H., Dumoulin, V., Courville, A.: \u201cFilm: Visual reasoning with a general conditioning layer,\u201d in Proceedings of the AAAI Conference on Artificial Intelligence, vol.\u00a032, no.\u00a01, (2018)","DOI":"10.1609\/aaai.v32i1.11671"},{"key":"3331_CR46","unstructured":"Sitzmann, V., Martel, J., Bergman, A., Lindell, D., Wetzstein, G.: Implicit neural representations with periodic activation functions. In: Advances in Neural Information Processing Systems, vol. 33, pp. 7462\u20137473 (2020)"},{"key":"3331_CR47","doi-asserted-by":"crossref","unstructured":"Kocabas, M., Huang, C.-H.\u00a0P., Hilliges, O., Black, M.\u00a0J.: \u201cPare: Part attention regressor for 3d human body estimation,\u201d in Proceedings of the IEEE\/CVF International Conference on Computer Vision, 11\u00a0127\u201311\u00a0137 (2021)","DOI":"10.1109\/ICCV48922.2021.01094"},{"key":"3331_CR48","unstructured":"Mescheder, L., Geiger, A., Nowozin, S.: \u201cWhich training methods for gans do actually converge?\u201d in International Conference on Machine Learning. PMLR, 3481\u20133490 (2018)"},{"issue":"3","key":"3331_CR49","doi-asserted-by":"publisher","first-page":"165","DOI":"10.1145\/964965.808594","volume":"18","author":"JT Kajiya","year":"1984","unstructured":"Kajiya, J.T., Von Herzen, B.P.: Ray tracing volume densities. ACM SIGGRAPH Comput. Graph. 18(3), 165\u2013174 (1984)","journal-title":"ACM SIGGRAPH Comput. Graph."},{"key":"3331_CR50","doi-asserted-by":"crossref","unstructured":"Richardson, E., Alaluf, Y., Patashnik, O., Nitzan, Y., Azar, Y., Shapiro, S., Cohen-Or, D.: \u201cEncoding in style: a stylegan encoder for image-to-image translation,\u201d in Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2287\u20132296 (2021)","DOI":"10.1109\/CVPR46437.2021.00232"},{"key":"3331_CR51","doi-asserted-by":"crossref","unstructured":"Lin, T.-Y., Doll\u00e1r, P., Girshick, R., He, K., Hariharan, B., Belongie, S.: \u201cFeature pyramid networks for object detection,\u201d in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2117\u20132125 (2017)","DOI":"10.1109\/CVPR.2017.106"},{"key":"3331_CR52","doi-asserted-by":"crossref","unstructured":"Chen, Y., Wu, Q., Zheng, C., Cham, T.-J., Cai, J.: \u201cSem2nerf: Converting single-view semantic masks to neural radiance fields,\u201d in European Conference on Computer Vision. Springer, 730\u2013748 (2022)","DOI":"10.1007\/978-3-031-19781-9_42"},{"key":"3331_CR53","doi-asserted-by":"crossref","unstructured":"Sun, J., Wang, X., Zhang, Y., Li, X., Zhang, Q., Liu, Y., Wang, J.: \u201cFenerf: Face editing in neural radiance fields,\u201d in Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 7672\u20137682 (2022)","DOI":"10.1109\/CVPR52688.2022.00752"},{"key":"3331_CR54","doi-asserted-by":"crossref","unstructured":"Zhang, R., Isola, P., Efros, A.\u00a0A., Shechtman, E., Wang, O.: \u201cThe unreasonable effectiveness of deep features as a perceptual metric,\u201d in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 586\u2013595 (2018)","DOI":"10.1109\/CVPR.2018.00068"},{"key":"3331_CR55","doi-asserted-by":"crossref","unstructured":"Liu, Z., Luo, P., Qiu, S., Wang, X., Tang, X.: \u201cDeepfashion: Powering robust clothes recognition and retrieval with rich annotations,\u201d in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 1096\u20131104 (2016)","DOI":"10.1109\/CVPR.2016.124"},{"key":"3331_CR56","doi-asserted-by":"crossref","unstructured":"Lin, K., Wang, L., Luo, K., Chen, Y., Liu, Z., Sun, M.-T.: Cross-domain complementary learning using pose for multi-person part segmentation. IEEE Trans. Circuits Syst. Video Technol. 31(3), 1066\u20131078 (2020)","DOI":"10.1109\/TCSVT.2020.2995122"},{"key":"3331_CR57","doi-asserted-by":"crossref","unstructured":"Cheong, S.\u00a0Y., Mustafa, A., Gilbert, A.: \u201cUpgpt: Universal diffusion model for person image generation, editing and pose transfer,\u201d arXiv preprintarXiv:2304.08870, (2023)","DOI":"10.1109\/ICCVW60793.2023.00451"},{"issue":"4","key":"3331_CR58","doi-asserted-by":"publisher","first-page":"600","DOI":"10.1109\/TIP.2003.819861","volume":"13","author":"Z Wang","year":"2004","unstructured":"Wang, Z., Bovik, A.C., Sheikh, H.R., Simoncelli, E.P.: Image quality assessment: from error visibility to structural similarity. IEEE Trans. Image Process. 13(4), 600\u2013612 (2004)","journal-title":"IEEE Trans. Image Process."},{"key":"3331_CR59","unstructured":"Heusel, M., Ramsauer, H., Unterthiner, T., Nessler, B., Hochreiter, S.: \u201cGans trained by a two time-scale update rule converge to a local nash equilibrium,\u201d In: Advances in neural information processing systems, 30, (2017)"},{"key":"3331_CR60","doi-asserted-by":"crossref","unstructured":"Bhunia, A.\u00a0K., Khan, S., Cholakkal, H., Anwer, R.\u00a0M., Laaksonen, J., Shah, M., Khan, F.\u00a0S.: \u201cPerson image synthesis via denoising diffusion model,\u201d in Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 5968\u20135976 (2023)","DOI":"10.1109\/CVPR52729.2023.00578"},{"key":"3331_CR61","doi-asserted-by":"crossref","unstructured":"He, K., Zhang, X., Ren, S., Sun, J.: \u201cDeep residual learning for image recognition,\u201d in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 770\u2013778 (2016)","DOI":"10.1109\/CVPR.2016.90"},{"key":"3331_CR62","unstructured":"Karras, T., Aila, T., Laine, S., Lehtinen, J.: \u201cProgressive growing of gans for improved quality, stability, and variation,\u201d arXiv preprintarXiv:1710.10196 (2017)"}],"container-title":["The Visual Computer"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00371-024-03331-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00371-024-03331-4\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00371-024-03331-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,1,24]],"date-time":"2025-01-24T13:01:25Z","timestamp":1737723685000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00371-024-03331-4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,4,2]]},"references-count":62,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2025,1]]}},"alternative-id":["3331"],"URL":"https:\/\/doi.org\/10.1007\/s00371-024-03331-4","relation":{},"ISSN":["0178-2789","1432-2315"],"issn-type":[{"type":"print","value":"0178-2789"},{"type":"electronic","value":"1432-2315"}],"subject":[],"published":{"date-parts":[[2024,4,2]]},"assertion":[{"value":"23 February 2024","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"2 April 2024","order":2,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}