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Generating high-quality and diverse human images is an important yet challenging task in vision and graphics.
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Lingjie Liu, Weipeng Xu, Michael Zollhoefer, Hyeongwoo Kim, Florian Bernard, Marc Habermann, Wenping Wang, and Christian Theobalt. 2019 · 2019
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Style and Pose Control for Image Synthesis of Humans from a Single Monocular View
Kripasindhu Sarkar, Vladislav Golyanik, Lingjie Liu, and Christian Theobalt. 2021a · 2021
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HumanGAN: A Generative Model of Human Images. In 2021 International Conference on 3D Vision (3DV) . IEEE, 258–267
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AgileGAN: stylizing portraits by inversion-consistent transfer learning
Guoxian Song, Linjie Luo, Jing Liu, Wan-Chun Ma, Chunpong Lai, Chuanxia Zheng, and Tat-Jen Cham. 2021 · 2021
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Pose-Guided Human Animation from a Single Image in the Wild. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition . 15039–15048
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HuMMan: Multi-Modal 4D Human Dataset for Versatile Sensing and Modeling
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InsetGAN for Full-Body Image Generation. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition
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StyleGAN-Human: A Data-Centric Odyssey of Human Generation
Jianglin Fu, Shikai Li, Yuming Jiang, Kwan-Yee Lin, Chen Qian, Chen-Change Loy, Wayne Wu, and Ziwei Liu. 2022 · 2022
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Vector quantized diffusion model for text-to-image synthesis. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition
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