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In this study, we introduce a methodology for human image animation by leveraging a 3D human parametric model within a latent diffusion framework to enhance shape alignment and motion guidance in curernt human generative techniques.
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He, T., Xu, Y., Saito, S., Soatto, S., Tung, T.: Arch++: Animation-ready clothed human reconstruction revisited. In: Proceedings of the IEEE/CVF International Conference on Computer Vision (2021)
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Bhunia, A.K., Khan, S., Cholakkal, H., Anwer, R.M., Laaksonen, J., Shah, M., Khan, F.S.: Person image synthesis via denoising diffusion model. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (2023)
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Prokudin, S., Black, M.J., Romero, J.: Smplpix: Neural avatars from 3d human models. In: Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision. pp. 1810–1819 (2021)
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Yoon, J.S., Liu, L., Golyanik, V., Sarkar, K., Park, H.S., Theobalt, C.: Pose-guided human animation from a single image in the wild (2021)
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2023
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Tseng, J., Castellon, R., Liu, K.: Edge: Editable dance generation from music. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (2023)
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Yang, Z., Zeng, A., Yuan, C., Li, Y.: Effective whole-body pose estimation with two-stages distillation. In: Proceedings of the IEEE/CVF International Conference on Computer Vision (2023)
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Yu, W.Y., Po, L.M., Cheung, R.C., Zhao, Y., Xue, Y., Li, K.: Bidirectionally deformable motion modulation for video-based human pose transfer. In: Proceedings of the IEEE/CVF International Conference on Computer Vision (2023)
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Zhang, L., Rao, A., Agrawala, M.: Adding conditional control to text-to-image diffusion models. In: Proceedings of the IEEE/CVF International Conference on Computer Vision (2023)
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