{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,24]],"date-time":"2026-06-24T16:17:21Z","timestamp":1782317841508,"version":"3.54.5"},"reference-count":87,"publisher":"Association for Computing Machinery (ACM)","issue":"4","license":[{"start":{"date-parts":[[2022,7,1]],"date-time":"2022-07-01T00:00:00Z","timestamp":1656633600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"RIE2020 Industry Alignment Fund Industry Collaboration Projects (IAF-ICP) Funding Initiative","award":["I1901E0052"],"award-info":[{"award-number":["I1901E0052"]}]},{"name":"NTU NAP, MOE AcRF Tier 2","award":["T2EP20221-0033"],"award-info":[{"award-number":["T2EP20221-0033"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Graph."],"published-print":{"date-parts":[[2022,7]]},"abstract":"<jats:p>3D avatar creation plays a crucial role in the digital age. However, the whole production process is prohibitively time-consuming and labor-intensive. To democratize this technology to a larger audience, we propose AvatarCLIP, a zero-shot text-driven framework for 3D avatar generation and animation. Unlike professional software that requires expert knowledge, AvatarCLIP empowers layman users to customize a 3D avatar with the desired shape and texture, and drive the avatar with the described motions using solely natural languages. Our key insight is to take advantage of the powerful vision-language model CLIP for supervising neural human generation, in terms of 3D geometry, texture and animation. Specifically, driven by natural language descriptions, we initialize 3D human geometry generation with a shape VAE network. Based on the generated 3D human shapes, a volume rendering model is utilized to further facilitate geometry sculpting and texture generation. Moreover, by leveraging the priors learned in the motion VAE, a CLIP-guided reference-based motion synthesis method is proposed for the animation of the generated 3D avatar. Extensive qualitative and quantitative experiments validate the effectiveness and generalizability of AvatarCLIP on a wide range of avatars. Remarkably, AvatarCLIP can generate unseen 3D avatars with novel animations, achieving superior zero-shot capability. Codes are available at https:\/\/github.com\/hongfz16\/AvatarCLIP.<\/jats:p>","DOI":"10.1145\/3528223.3530094","type":"journal-article","created":{"date-parts":[[2022,7,22]],"date-time":"2022-07-22T21:06:27Z","timestamp":1658523987000},"page":"1-19","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":231,"title":["AvatarCLIP"],"prefix":"10.1145","volume":"41","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2412-1141","authenticated-orcid":false,"given":"Fangzhou","family":"Hong","sequence":"first","affiliation":[{"name":"Nanyang Technological University, Singapore"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8212-715X","authenticated-orcid":false,"given":"Mingyuan","family":"Zhang","sequence":"additional","affiliation":[{"name":"Nanyang Technological University, Singapore"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1821-4296","authenticated-orcid":false,"given":"Liang","family":"Pan","sequence":"additional","affiliation":[{"name":"Nanyang Technological University, Singapore"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1810-3855","authenticated-orcid":false,"given":"Zhongang","family":"Cai","sequence":"additional","affiliation":[{"name":"Nanyang Technological University, Singapore and SenseTime Research, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0571-5924","authenticated-orcid":false,"given":"Lei","family":"Yang","sequence":"additional","affiliation":[{"name":"SenseTime Research, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4220-5958","authenticated-orcid":false,"given":"Ziwei","family":"Liu","sequence":"additional","affiliation":[{"name":"Nanyang Technological University, Singapore"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2022,7,22]]},"reference":[{"key":"e_1_2_2_1_1","volume-title":"Dance2Music: Automatic Dance-driven Music Generation. arXiv preprint arXiv:2107.06252","author":"Aggarwal Gunjan","year":"2021","unstructured":"Gunjan Aggarwal and Devi Parikh. 2021. Dance2Music: Automatic Dance-driven Music Generation. arXiv preprint arXiv:2107.06252 (2021)."},{"key":"e_1_2_2_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2018.8460608"},{"key":"e_1_2_2_3_1","doi-asserted-by":"publisher","DOI":"10.1109\/3DV.2019.00084"},{"key":"e_1_2_2_4_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00875"},{"key":"e_1_2_2_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/3355089.3356536"},{"key":"e_1_2_2_6_1","volume-title":"Proceedings, Part II 16","author":"Bhatnagar Bharat Lal","year":"2020","unstructured":"Bharat Lal Bhatnagar, Cristian Sminchisescu, Christian Theobalt, and Gerard Pons-Moll. 2020. Combining implicit function learning and parametric models for 3d human reconstruction. In Computer Vision-ECCV 2020: 16th European Conference, Glasgow, UK, August 23--28, 2020, Proceedings, Part II 16. Springer, 311--329."},{"key":"e_1_2_2_7_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00552"},{"key":"e_1_2_2_8_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.01058"},{"key":"e_1_2_2_9_1","volume-title":"Lei Yang, and Ziwei Liu.","author":"Cai Zhongang","year":"2022","unstructured":"Zhongang Cai, Daxuan Ren, Ailing Zeng, Zhengyu Lin, Tao Yu, Wenjia Wang, Xiangyu Fan, Yang Gao, Yifan Yu, Liang Pan, Fangzhou Hong, Mingyuan Zhang, Chen Change Loy, Lei Yang, and Ziwei Liu. 2022. HuMMan: Multi-Modal 4D Human Dataset for Versatile Sensing and Modeling. arXiv preprint arXiv:2204.13686 (2022)."},{"key":"e_1_2_2_10_1","unstructured":"Zhongang Cai Mingyuan Zhang Jiawei Ren Chen Wei Daxuan Ren Jiatong Li Zhengyu Lin Haiyu Zhao Shuai Yi Lei Yang et al. 2021. Playing for 3D Human Recovery. arXiv preprint arXiv:2110.07588 (2021)."},{"key":"e_1_2_2_11_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00574"},{"key":"e_1_2_2_12_1","volume-title":"gDNA: Towards Generative Detailed Neural Avatars. arXiv","author":"Chen Xu","year":"2022","unstructured":"Xu Chen, Tianjian Jiang, Jie Song, Jinlong Yang, Michael J Black, Andreas Geiger, and Otmar Hilliges. 2022. gDNA: Towards Generative Detailed Neural Avatars. arXiv (2022)."},{"key":"e_1_2_2_13_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01170"},{"key":"e_1_2_2_14_1","volume-title":"Density estimation using real nvp. arXiv preprint arXiv:1605.08803","author":"Dinh Laurent","year":"2016","unstructured":"Laurent Dinh, Jascha Sohl-Dickstein, and Samy Bengio. 2016. Density estimation using real nvp. arXiv preprint arXiv:1605.08803 (2016)."},{"key":"e_1_2_2_15_1","volume-title":"Clipdraw: Exploring text-to-drawing synthesis through language-image encoders. arXiv preprint arXiv:2106.14843","author":"Frans Kevin","year":"2021","unstructured":"Kevin Frans, LB Soros, and Olaf Witkowski. 2021. Clipdraw: Exploring text-to-drawing synthesis through language-image encoders. arXiv preprint arXiv:2106.14843 (2021)."},{"key":"e_1_2_2_16_1","volume-title":"StyleGAN-Human: A Data-Centric Odyssey of Human Generation. arXiv preprint arXiv:2204.11823","author":"Fu Jianglin","year":"2022","unstructured":"Jianglin Fu, Shikai Li, Yuming Jiang, Kwan-Yee Lin, Chen Qian, Chen-Change Loy, Wayne Wu, and Ziwei Liu. 2022. StyleGAN-Human: A Data-Centric Odyssey of Human Generation. arXiv preprint arXiv:2204.11823 (2022)."},{"key":"e_1_2_2_17_1","doi-asserted-by":"publisher","DOI":"10.1145\/3450618.3469163"},{"key":"e_1_2_2_18_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00511"},{"key":"e_1_2_2_19_1","volume-title":"Implicit geometric regularization for learning shapes. arXiv preprint arXiv:2002.10099","author":"Gropp Amos","year":"2020","unstructured":"Amos Gropp, Lior Yariv, Niv Haim, Matan Atzmon, and Yaron Lipman. 2020. Implicit geometric regularization for learning shapes. arXiv preprint arXiv:2002.10099 (2020)."},{"key":"e_1_2_2_20_1","doi-asserted-by":"publisher","DOI":"10.1145\/3394171.3413635"},{"key":"e_1_2_2_21_1","doi-asserted-by":"publisher","DOI":"10.1145\/3450626.3459749"},{"key":"e_1_2_2_22_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00787"},{"key":"e_1_2_2_23_1","unstructured":"Fangzhou Hong Liang Pan Zhongang Cai and Ziwei Liu. 2021. Garment4D: Garment Reconstruction from Point Cloud Sequences. In Advances in Neural Information Processing Systems."},{"key":"e_1_2_2_24_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01568"},{"key":"e_1_2_2_25_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00316"},{"key":"e_1_2_2_26_1","doi-asserted-by":"publisher","DOI":"10.1145\/1477926.1477927"},{"key":"e_1_2_2_27_1","volume-title":"6m: Large scale datasets and predictive methods for 3d human sensing in natural environments","author":"Ionescu Catalin","year":"2013","unstructured":"Catalin Ionescu, Dragos Papava, Vlad Olaru, and Cristian Sminchisescu. 2013. Human3. 6m: Large scale datasets and predictive methods for 3d human sensing in natural environments. IEEE transactions on pattern analysis and machine intelligence 36, 7 (2013), 1325--1339."},{"key":"e_1_2_2_28_1","volume-title":"Zero-Shot Text-Guided Object Generation with Dream Fields. arXiv preprint arXiv:2112.01455","author":"Jain Ajay","year":"2021","unstructured":"Ajay Jain, Ben Mildenhall, Jonathan T Barron, Pieter Abbeel, and Ben Poole. 2021a. Zero-Shot Text-Guided Object Generation with Dream Fields. arXiv preprint arXiv:2112.01455 (2021)."},{"key":"e_1_2_2_29_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00583"},{"key":"e_1_2_2_30_1","volume-title":"ClipMatrix: Text-controlled Creation of 3D Textured Meshes. arXiv preprint arXiv:2109.12922","author":"Jetchev Nikolay","year":"2021","unstructured":"Nikolay Jetchev. 2021. ClipMatrix: Text-controlled Creation of 3D Textured Meshes. arXiv preprint arXiv:2109.12922 (2021)."},{"key":"e_1_2_2_31_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58565-5_2"},{"key":"e_1_2_2_32_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.01354"},{"key":"e_1_2_2_33_1","doi-asserted-by":"publisher","DOI":"10.1145\/3550454.3555513"},{"key":"e_1_2_2_34_1","volume-title":"TrajeVAE-Controllable Human Motion Generation from Trajectories. arXiv preprint arXiv:2104.00351","author":"Kania Kacper","year":"2021","unstructured":"Kacper Kania, Marek Kowalski, and Tomasz Trzci\u0144ski. 2021. TrajeVAE-Controllable Human Motion Generation from Trajectories. arXiv preprint arXiv:2104.00351 (2021)."},{"key":"e_1_2_2_35_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00453"},{"key":"e_1_2_2_36_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00813"},{"key":"e_1_2_2_37_1","volume-title":"Adam: A method for stochastic optimization. arXiv preprint arXiv:1412.6980","author":"Kingma Diederik P","year":"2014","unstructured":"Diederik P Kingma and Jimmy Ba. 2014. Adam: A method for stochastic optimization. arXiv preprint arXiv:1412.6980 (2014)."},{"key":"e_1_2_2_38_1","volume-title":"Auto-encoding variational bayes. arXiv preprint arXiv:1312.6114","author":"Kingma Diederik P","year":"2013","unstructured":"Diederik P Kingma and Max Welling. 2013. Auto-encoding variational bayes. arXiv preprint arXiv:1312.6114 (2013)."},{"key":"e_1_2_2_39_1","doi-asserted-by":"publisher","DOI":"10.1145\/3450626.3459884"},{"key":"e_1_2_2_40_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.01315"},{"key":"e_1_2_2_41_1","doi-asserted-by":"publisher","DOI":"10.1145\/3386569.3392422"},{"key":"e_1_2_2_42_1","first-page":"1","article-title":"Neural actor: Neural free-view synthesis of human actors with pose control","volume":"40","author":"Liu Lingjie","year":"2021","unstructured":"Lingjie Liu, Marc Habermann, Viktor Rudnev, Kripasindhu Sarkar, Jiatao Gu, and Christian Theobalt. 2021. Neural actor: Neural free-view synthesis of human actors with pose control. ACM Transactions on Graphics (TOG) 40, 6 (2021), 1--16.","journal-title":"ACM Transactions on Graphics (TOG)"},{"key":"e_1_2_2_43_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.425"},{"key":"e_1_2_2_44_1","doi-asserted-by":"publisher","DOI":"10.1145\/2816795.2818013"},{"key":"e_1_2_2_45_1","volume-title":"Marching cubes: A high resolution 3D surface construction algorithm. ACM siggraph computer graphics 21, 4","author":"Lorensen William E","year":"1987","unstructured":"William E Lorensen and Harvey E Cline. 1987. Marching cubes: A high resolution 3D surface construction algorithm. ACM siggraph computer graphics 21, 4 (1987), 163--169."},{"key":"e_1_2_2_46_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00554"},{"key":"e_1_2_2_47_1","volume-title":"Jimmy Lei Ba, and Ruslan Salakhutdinov","author":"Mansimov Elman","year":"2015","unstructured":"Elman Mansimov, Emilio Parisotto, Jimmy Lei Ba, and Ruslan Salakhutdinov. 2015. Generating images from captions with attention. arXiv preprint arXiv:1511.02793 (2015)."},{"key":"e_1_2_2_48_1","doi-asserted-by":"publisher","DOI":"10.1109\/3DV.2017.00064"},{"key":"e_1_2_2_49_1","volume-title":"Text2Mesh: Text-Driven Neural Stylization for Meshes. arXiv preprint arXiv:2112.03221","author":"Michel Oscar","year":"2021","unstructured":"Oscar Michel, Roi Bar-On, Richard Liu, Sagie Benaim, and Rana Hanocka. 2021. Text2Mesh: Text-Driven Neural Stylization for Meshes. arXiv preprint arXiv:2112.03221 (2021)."},{"key":"e_1_2_2_50_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01032"},{"key":"e_1_2_2_51_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58452-8_24"},{"key":"e_1_2_2_52_1","doi-asserted-by":"publisher","DOI":"10.1145\/1073204.1073313"},{"key":"e_1_2_2_53_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00571"},{"key":"e_1_2_2_54_1","volume-title":"Unsupervised Learning of Efficient Geometry-Aware Neural Articulated Representations. arXiv preprint arXiv:2204.08839","author":"Noguchi Atsuhiro","year":"2022","unstructured":"Atsuhiro Noguchi, Xiao Sun, Stephen Lin, and Tatsuya Harada. 2022. Unsupervised Learning of Efficient Geometry-Aware Neural Articulated Representations. arXiv preprint arXiv:2204.08839 (2022)."},{"key":"e_1_2_2_55_1","volume-title":"NPMs: Neural Parametric Models for 3D Deformable Shapes. arXiv preprint arXiv:2104.00702","author":"Palafox Pablo","year":"2021","unstructured":"Pablo Palafox, Alja\u017e Bo\u017ei\u010d, Justus Thies, Matthias Nie\u00dfner, and Angela Dai. 2021. NPMs: Neural Parametric Models for 3D Deformable Shapes. arXiv preprint arXiv:2104.00702 (2021)."},{"key":"e_1_2_2_56_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00209"},{"key":"e_1_2_2_57_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.01123"},{"key":"e_1_2_2_58_1","volume-title":"Animatable neural radiance fields for human body modeling. arXiv e-prints","author":"Peng Sida","year":"2021","unstructured":"Sida Peng, Junting Dong, Qianqian Wang, Shangzhan Zhang, Qing Shuai, Hujun Bao, and Xiaowei Zhou. 2021a. Animatable neural radiance fields for human body modeling. arXiv e-prints (2021), arXiv-2105."},{"key":"e_1_2_2_59_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00894"},{"key":"e_1_2_2_60_1","volume-title":"Action-Conditioned 3D Human Motion Synthesis with Transformer VAE. arXiv preprint arXiv:2104.05670","author":"Petrovich Mathis","year":"2021","unstructured":"Mathis Petrovich, Michael J Black, and G\u00fcl Varol. 2021. Action-Conditioned 3D Human Motion Synthesis with Transformer VAE. arXiv preprint arXiv:2104.05670 (2021)."},{"key":"e_1_2_2_61_1","volume-title":"Building Statistical Shape Spaces for 3D Human Modeling. Pattern Recognition","author":"Pishchulin Leonid","year":"2017","unstructured":"Leonid Pishchulin, Stefanie Wuhrer, Thomas Helten, Christian Theobalt, and Bernt Schiele. 2017. Building Statistical Shape Spaces for 3D Human Modeling. Pattern Recognition (2017)."},{"key":"e_1_2_2_62_1","volume-title":"Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et al.","author":"Radford Alec","year":"2021","unstructured":"Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et al. 2021. Learning transferable visual models from natural language supervision. arXiv preprint arXiv:2103.00020 (2021)."},{"key":"e_1_2_2_63_1","volume-title":"Zero-shot text-to-image generation. arXiv preprint arXiv:2102.12092","author":"Ramesh Aditya","year":"2021","unstructured":"Aditya Ramesh, Mikhail Pavlov, Gabriel Goh, Scott Gray, Chelsea Voss, Alec Radford, Mark Chen, and Ilya Sutskever. 2021. Zero-shot text-to-image generation. arXiv preprint arXiv:2102.12092 (2021)."},{"key":"e_1_2_2_64_1","volume-title":"International Conference on Machine Learning. PMLR, 1060--1069","author":"Reed Scott","year":"2016","unstructured":"Scott Reed, Zeynep Akata, Xinchen Yan, Lajanugen Logeswaran, Bernt Schiele, and Honglak Lee. 2016. Generative adversarial text to image synthesis. In International Conference on Machine Learning. PMLR, 1060--1069."},{"key":"e_1_2_2_65_1","doi-asserted-by":"publisher","DOI":"10.1109\/38.708559"},{"key":"e_1_2_2_66_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00291"},{"key":"e_1_2_2_67_1","volume-title":"Clip-forge: Towards zero-shot text-to-shape generation. arXiv preprint arXiv:2110.02624","author":"Sanghi Aditya","year":"2021","unstructured":"Aditya Sanghi, Hang Chu, Joseph G Lambourne, Ye Wang, Chin-Yi Cheng, and Marco Fumero. 2021. Clip-forge: Towards zero-shot text-to-shape generation. arXiv preprint arXiv:2110.02624 (2021)."},{"key":"e_1_2_2_68_1","volume-title":"Style and pose control for image synthesis of humans from a single monocular view. arXiv preprint arXiv:2102.11263","author":"Sarkar Kripasindhu","year":"2021","unstructured":"Kripasindhu Sarkar, Vladislav Golyanik, Lingjie Liu, and Christian Theobalt. 2021a. Style and pose control for image synthesis of humans from a single monocular view. arXiv preprint arXiv:2102.11263 (2021)."},{"key":"e_1_2_2_69_1","volume-title":"HumanGAN: A Generative Model of Humans Images. arXiv preprint arXiv:2103.06902","author":"Sarkar Kripasindhu","year":"2021","unstructured":"Kripasindhu Sarkar, Lingjie Liu, Vladislav Golyanik, and Christian Theobalt. 2021b. HumanGAN: A Generative Model of Humans Images. arXiv preprint arXiv:2103.06902 (2021)."},{"key":"e_1_2_2_70_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00248"},{"key":"e_1_2_2_71_1","first-page":"7137","article-title":"First order motion model for image animation","volume":"32","author":"Siarohin Aliaksandr","year":"2019","unstructured":"Aliaksandr Siarohin, St\u00e9phane Lathuili\u00e8re, Sergey Tulyakov, Elisa Ricci, and Nicu Sebe. 2019b. First order motion model for image animation. Advances in Neural Information Processing Systems 32 (2019), 7137--7147.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_2_2_72_1","volume-title":"MotionCLIP: Exposing Human Motion Generation to CLIP Space. arXiv preprint arXiv:2203.08063","author":"Tevet Guy","year":"2022","unstructured":"Guy Tevet, Brian Gordon, Amir Hertz, Amit H Bermano, and Daniel Cohen-Or. 2022. MotionCLIP: Exposing Human Motion Generation to CLIP Space. arXiv preprint arXiv:2203.08063 (2022)."},{"key":"e_1_2_2_73_1","unstructured":"Ayush Tewari Justus Thies Ben Mildenhall Pratul Srinivasan Edgar Tretschk Yifan Wang Christoph Lassner Vincent Sitzmann Ricardo Martin-Brualla Stephen Lombardi et al. 2021. Advances in neural rendering. arXiv preprint arXiv:2111.05849 (2021)."},{"key":"e_1_2_2_74_1","doi-asserted-by":"crossref","unstructured":"G\u00fcl Varol Javier Romero Xavier Martin Naureen Mahmood Michael J. Black Ivan Laptev and Cordelia Schmid. 2017. Learning from Synthetic Humans. In CVPR.","DOI":"10.1109\/CVPR.2017.492"},{"key":"e_1_2_2_75_1","unstructured":"Ashish Vaswani Noam Shazeer Niki Parmar Jakob Uszkoreit Llion Jones Aidan N Gomez \u0141ukasz Kaiser and Illia Polosukhin. 2017. Attention is all you need. In Advances in neural information processing systems. 5998--6008."},{"key":"e_1_2_2_76_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01249-6_37"},{"key":"e_1_2_2_77_1","volume-title":"CLIPNeRF: Text-and-Image Driven Manipulation of Neural Radiance Fields. arXiv preprint arXiv:2112.05139","author":"Wang Can","year":"2021","unstructured":"Can Wang, Menglei Chai, Mingming He, Dongdong Chen, and Jing Liao. 2021a. CLIPNeRF: Text-and-Image Driven Manipulation of Neural Radiance Fields. arXiv preprint arXiv:2112.05139 (2021)."},{"key":"e_1_2_2_78_1","volume-title":"NeuS: Learning Neural Implicit Surfaces by","author":"Wang Peng","year":"2021","unstructured":"Peng Wang, Lingjie Liu, Yuan Liu, Christian Theobalt, Taku Komura, and Wenping Wang. 2021b. NeuS: Learning Neural Implicit Surfaces by Volume Rendering for Multi-view Reconstruction. arXiv preprint arXiv:2106.10689 (2021)."},{"key":"e_1_2_2_79_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00606"},{"key":"e_1_2_2_80_1","doi-asserted-by":"publisher","DOI":"10.1145\/3355089.3356499"},{"key":"e_1_2_2_81_1","volume-title":"Amer Xiao Lin","author":"Mohamed","year":"2014","unstructured":"Mohamed R. Amer Xiao Lin. 2014. Human Motion Modeling using DVGANs. arXiv preprint arXiv:1804.10652 (2014)."},{"key":"e_1_2_2_82_1","volume-title":"H-nerf: Neural radiance fields for rendering and temporal reconstruction of humans in motion. Advances in Neural Information Processing Systems 34","author":"Xu Hongyi","year":"2021","unstructured":"Hongyi Xu, Thiemo Alldieck, and Cristian Sminchisescu. 2021a. H-nerf: Neural radiance fields for rendering and temporal reconstruction of humans in motion. Advances in Neural Information Processing Systems 34 (2021)."},{"key":"e_1_2_2_83_1","volume-title":"A Simple Baseline for Zero-shot Semantic Segmentation with Pre-trained Vision-language Model. arXiv preprint arXiv:2112.14757","author":"Xu Mengde","year":"2021","unstructured":"Mengde Xu, Zheng Zhang, Fangyun Wei, Yutong Lin, Yue Cao, Han Hu, and Xiang Bai. 2021b. A Simple Baseline for Zero-shot Semantic Segmentation with Pre-trained Vision-language Model. arXiv preprint arXiv:2112.14757 (2021)."},{"key":"e_1_2_2_84_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01479"},{"key":"e_1_2_2_85_1","volume-title":"3D-Aware Semantic-Guided Generative Model for Human Synthesis. arXiv preprint arXiv:2112.01422","author":"Zhang Jichao","year":"2021","unstructured":"Jichao Zhang, Enver Sangineto, Hao Tang, Aliaksandr Siarohin, Zhun Zhong, Nicu Sebe, and Wei Wang. 2021. 3D-Aware Semantic-Guided Generative Model for Human Synthesis. arXiv preprint arXiv:2112.01422 (2021)."},{"key":"e_1_2_2_86_1","volume-title":"HumanNeRF: Generalizable Neural Human Radiance Field from Sparse Inputs. arXiv preprint arXiv:2112.02789","author":"Zhao Fuqiang","year":"2021","unstructured":"Fuqiang Zhao, Wei Yang, Jiakai Zhang, Pei Lin, Yingliang Zhang, Jingyi Yu, and Lan Xu. 2021. HumanNeRF: Generalizable Neural Human Radiance Field from Sparse Inputs. arXiv preprint arXiv:2112.02789 (2021)."},{"key":"e_1_2_2_87_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00589"}],"container-title":["ACM Transactions on Graphics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3528223.3530094","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3528223.3530094","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T19:02:26Z","timestamp":1750186946000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3528223.3530094"}},"subtitle":["zero-shot text-driven generation and animation of 3D avatars"],"short-title":[],"issued":{"date-parts":[[2022,7]]},"references-count":87,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2022,7]]}},"alternative-id":["10.1145\/3528223.3530094"],"URL":"https:\/\/doi.org\/10.1145\/3528223.3530094","relation":{},"ISSN":["0730-0301","1557-7368"],"issn-type":[{"value":"0730-0301","type":"print"},{"value":"1557-7368","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,7]]},"assertion":[{"value":"2022-07-22","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}