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In this work, we propose MagicPose, a diffusion-based model for 2D human pose and facial expression retargeting.
Feature-based image metamorphosis
Beier, T. and Neely, S · 1992
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Video rewrite: Driving visual speech with audio
Bregler, C., Covell, M., and Slaney, M · 1997
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Image inpainting
Bertalmio, M., Sapiro, G., Caselles, V., and Ballester, C · 2000
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Recognizing action at a distance
Efros, Berg, Mori, and Malik · 2003
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Markerless human motion transfer
Cheung, G., Baker, S., Hodgins, J., and Kanade, T · 2004
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Image quality assessment: from error visibility to structural similarity
Wang, Z., Bovik, A. C., Sheikh, H. R., and Simoncelli, E. P · 2004
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Image quality metrics: Psnr vs. ssim
Hore, A. and Ziou, D · 2010
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Video-based characters: Creating new human performances from a multi-view video database
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Microsoft coco: Common objects in context
Lin, T.-Y., Maire, M., Belongie, S., Hays, J., Perona, P., Ramanan, D., Dollár, P., and Zitnick, C. L · 2014
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Conditional generative adversarial nets, 2014
Mirza, M. and Osindero, S · 2014
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U-net: Convolutional networks for biomedical image segmentation
Ronneberger, O., Fischer, P., and Brox, T · 2015
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Convolutional pose machines
Wei, S.-E., Ramakrishna, V., Kanade, T., and Sheikh, Y · 2016
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Realtime multi-person 2d pose estimation using part affinity fields
Cao, Z., Simon, T., Wei, S.-E., and Sheikh, Y · 2017
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Gans trained by a two time-scale update rule converge to a local nash equilibrium
Heusel, M., Ramsauer, H., Unterthiner, T., Nessler, B., and Hochreiter, S · 2017
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Hand keypoint detection in single images using multiview bootstrapping
Simon, T., Joo, H., Matthews, I., and Sheikh, Y · 2017
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Neural discrete representation learning
Van Den Oord, A., Vinyals, O., et al · 2017
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Semantic image inpainting with deep generative models
Yeh, R. A., Chen, C., Yian Lim, T., Schwing, A. G., Hasegawa-Johnson, M., and Do, M. N · 2017
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Deep video portraits
Kim, H., Garrido, P., Tewari, A., Xu, W., Thies, J., Nießner, M., Pérez, P., Richardt, C., Zollöfer, M., and Theobalt, C · 2018
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Geometry-contrastive gan for facial expression transfer
Qiao, F., Yao, N., Jiao, Z., Li, Z., Chen, H., and Wang, H · 2018
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Deformable gans for pose-based human image generation
Siarohin, A., Sangineto, E., Lathuilière, S., and Sebe, N · 2018
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MoCoGAN: Decomposing motion and content for video generation
Tulyakov, S., Liu, M.-Y., Yang, X., and Kautz, J · 2018
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The unreasonable effectiveness of deep features as a perceptual metric
Zhang, R., Isola, P., Efros, A. A., Shechtman, E., and Wang, O · 2018
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Openpose: Realtime multi-person 2d pose estimation using part affinity fields
Cao, Z., Hidalgo Martinez, G., Simon, T., Wei, S., and Sheikh, Y. A · 2019
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Deepfashion2: A versatile benchmark for detection, pose estimation, segmentation and re-identification of clothing images
Ge, Y., Zhang, R., Wang, X., Tang, X., and Luo, P · 2019
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Liquid warping gan: A unified framework for human motion imitation, appearance transfer and novel view synthesis
Liu, W., Piao, Z., Min, J., Luo, W., Ma, L., and Gao, S · 2019
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Denoising diffusion probabilistic models
Ho, J., Jain, A., and Abbeel, P · 2020
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Score-based generative modeling through stochastic differential equations
Song, Y., Sohl-Dickstein, J., Kingma, D. P., Kumar, A., Ermon, S., and Poole, B · 2020
Depth-aware generative adversarial network for talking head video generation
Hong, F.-T., Zhang, L., Shen, L., and Xu, D · 2022
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Stable Diffusion Image Variations
Justin, P. and Lambda · 2022
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Adaface: Quality adaptive margin for face recognition
Kim, M., Jain, A. K., and Liu, X · 2022
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Repaint: Inpainting using denoising diffusion probabilistic models
Lugmayr, A., Danelljan, M., Romero, A., Yu, F., Timofte, R., and Van Gool, L · 2022
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Dreamfusion: Text-to-3d using 2d diffusion
Poole, B., Jain, A., Barron, J. T., and Mildenhall, B · 2022
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Hierarchical text-conditional image generation with clip latents, 2022
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Cited alongside, same era.
Gac-gan: A general method for appearance-controllable human video motion transfer
Wei, D., Xu, X., Shen, H., and Huang, K · 2020
Cited alongside, same era.
Cascade ef-gan: Progressive facial expression editing with local focuses
Wu, R., Zhang, G., Lu, S., and Chen, T · 2020
Cited alongside, same era.
Pose with Style: Detail-preserving pose-guided image synthesis with conditional stylegan
AlBahar, B., Lu, J., Yang, J., Shu, Z., Shechtman, E., and Huang, J.-B · 2021
Cited alongside, same era.
Segdiff: Image segmentation with diffusion probabilistic models
Amit, T., Shaharbany, T., Nachmani, E., and Wolf, L · 2021
Cited alongside, same era.
Label-efficient semantic segmentation with diffusion models
Baranchuk, D., Rubachev, I., Voynov, A., Khrulkov, V., and Babenko, A · 2021
Cited alongside, same era.
Learning high fidelity depths of dressed humans by watching social media dance videos
Jafarian, Y. and Park, H. S · 2021
Cited alongside, same era.
A comprehensive review of past and present image inpainting methods
Jam, J., Kendrick, C., Walker, K., Drouard, V., Hsu, J. G.-S., and Yap, M. H · 2021
Cited alongside, same era.
Ramesh, A., Dhariwal, P., Nichol, A., Chu, C., and Chen, M · 2022
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High-resolution image synthesis with latent diffusion models
Rombach, R., Blattmann, A., Lorenz, D., Esser, P., and Ommer, B · 2022
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Palette: Image-to-image diffusion models
Saharia, C., Chan, W., Chang, H., Lee, C., Ho, J., Salimans, T., Fleet, D., and Norouzi, M · 2022
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Make-a-video: Text-to-video generation without text-video data
Singer, U., Polyak, A., Hayes, T., Yin, X., An, J., Zhang, S., Hu, Q., Yang, H., Ashual, O., Gafni, O., et al · 2022
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Human motion transfer with 3d constraints and detail enhancement
Sun, Y.-T., Fu, Q.-C., Jiang, Y.-R., Liu, Z., Lai, Y.-K., Fu, H., and Gao, L · 2022
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Diffusion models for implicit image segmentation ensembles
Wolleb, J., Sandkühler, R., Bieder, F., Valmaggia, P., and Cattin, P. C · 2022
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Thin-plate spline motion model for image animation
Zhao, J. and Zhang, H · 2022
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Align your latents: High-resolution video synthesis with latent diffusion models
Blattmann, A., Rombach, R., Ling, H., Dockhorn, T., Kim, S. W., Fidler, S., and Kreis, K · 2023
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Masactrl: Tuning-free mutual self-attention control for consistent image synthesis and editing
Cao, M., Wang, X., Qi, Z., Shan, Y., Qie, X., and Zheng, Y · 2023
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Animatediff: Animate your personalized text-to-image diffusion models without specific tuning
Guo, Y., Yang, C., Rao, A., Wang, Y., Qiao, Y., Lin, D., and Dai, B · 2023
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Dreampose: Fashion image-to-video synthesis via stable diffusion
Karras, J., Holynski, A., Wang, T.-C., and Kemelmacher-Shlizerman, I · 2023
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Dreambooth3d: Subject-driven text-to-3d generation
Raj, A., Kaza, S., Poole, B., Niemeyer, M., Ruiz, N., Mildenhall, B., Zada, S., Aberman, K., Rubinstein, M., Barron, J., et al · 2023
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Mvdream: Multi-view diffusion for 3d generation
Shi, Y., Wang, P., Ye, J., Long, M., Li, K., and Yang, X · 2023
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Disco: Disentangled control for referring human dance generation in real world
Wang, T., Li, L., Lin, K., Lin, C.-C., Yang, Z., Zhang, H., Liu, Z., and Wang, L · 2023
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Tune-a-video: One-shot tuning of image diffusion models for text-to-video generation
Wu, J. Z., Ge, Y., Wang, X., Lei, S. W., Gu, Y., Shi, Y., Hsu, W., Shan, Y., Qie, X., and Shou, M. Z · 2023
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Adding conditional control to text-to-image diffusion models, 2023
Zhang, L., Rao, A., and Agrawala, M · 2023
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