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In recent years, generative artificial intelligence has achieved significant advancements in the field of image generation, spawning a variety of applications.
Image quality assessment: from error visibility to structural similarity
Wang, Z., Bovik, A. C., Sheikh, H. R., and Simoncelli, E. P · 2004
Earlier work this paper cites.
Towards accurate generative models of video: A new metric & challenges
Unterthiner, T., Van Steenkiste, S., Kurach, K., Marinier, R., Michalski, M., and Gelly, S · 2018
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Conditional gan with discriminative filter generation for text-to-video synthesis
Balaji, Y., Min, M. R., Bai, B., Chellappa, R., and Graf, H. P · 2019
Earlier work this paper cites.
Everybody dance now
Chan, C., Ginosar, S., Zhou, T., and Efros, A. A · 2019
Earlier work this paper cites.
First order motion model for image animation
Siarohin, A., Lathuilière, S., Tulyakov, S., Ricci, E., and Sebe, N · 2019
Earlier work this paper cites.
Denoising diffusion probabilistic models
Ho, J., Jain, A., and Abbeel, P · 2020
Earlier work this paper cites.
Score-based generative modeling through stochastic differential equations
Song, Y., Sohl-Dickstein, J., Kingma, D. P., Kumar, A., Ermon, S., and Poole, B · 2020
Earlier work this paper cites.
Learning high fidelity depths of dressed humans by watching social media dance videos
Jafarian, Y. and Park, H. S · 2021
Earlier work this paper cites.
Learning transferable visual models from natural language supervision
Radford, A., Kim, J. W., Hallacy, C., Ramesh, A., Goh, G., Agarwal, S., Sastry, G., Askell, A., Mishkin, P., Clark, J., et al · 2021
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Motion representations for articulated animation
Siarohin, A., Woodford, O. J., Ren, J., Chai, M., and Tulyakov, S · 2021
Earlier work this paper cites.
Videogpt: Video generation using vq-vae and transformers
Yan, W., Zhang, Y., Abbeel, P., and Srinivas, A · 2021
Earlier work this paper cites.
Latent video diffusion models for high-fidelity long video generation
He, Y., Yang, T., Zhang, Y., Shan, Y., and Chen, Q · 2022
Earlier work this paper cites.
Video diffusion models
Ho, J., Salimans, T., Gritsenko, A., Chan, W., Norouzi, M., and Fleet, D. J · 2022
Earlier work this paper cites.
Elucidating the Design Space of Diffusion-Based Generative Models, October 2022
Karras, T., Aittala, M., Aila, T., and Laine, S · 2022
Earlier work this paper cites.
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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Mcvd-masked conditional video diffusion for prediction, generation, and interpolation
Voleti, V., Jolicoeur-Martineau, A., and Pal, C · 2022
Cited alongside, same era.
Thin-plate spline motion model for image animation
Zhao, J. and Zhang, H · 2022
Cited alongside, same era.
Multidiffusion: Fusing diffusion paths for controlled image generation
Bar-Tal, O., Yariv, L., Lipman, Y., and Dekel, T · 2023
Cited alongside, same era.
Stable video diffusion: Scaling latent video diffusion models to large datasets
Blattmann, A., Dockhorn, T., Kulal, S., Mendelevitch, D., Kilian, M., Lorenz, D., Levi, Y., English, Z., Voleti, V., Letts, A., et al · 2023
Cited alongside, same era.
Magicpose: Realistic human poses and facial expressions retargeting with identity-aware diffusion
Chang, D., Shi, Y., Gao, Q., Xu, H., Fu, J., Song, G., Yan, Q., Zhu, Y., Yang, X., and Soleymani, M · 2023
Adding conditional control to text-to-image diffusion models
Zhang, L., Rao, A., and Agrawala, M · 2023
Later among the works it cites.
Champ: Controllable and consistent human image animation with 3d parametric guidance, 2024
Zhu, S., Chen, J. L., Dai, Z., Xu, Y., Cao, X., Yao, Y., Zhu, H., and Zhu, S · 2023
Later among the works it cites.
URL https://github.com/MooreThreads/Moore-AnimateAnyone
MooreThreads/Moore-AnimateAnyone, May 2024 · 2024
Closest in time.
Vidu: a highly consistent, dynamic and skilled text-to-video generator with diffusion models
Bao, F., Xiang, C., Yue, G., He, G., Zhu, H., Zheng, K., Zhao, M., Liu, S., Wang, Y., and Zhu, J · 2024
Closest in time.
Lumiere: A space-time diffusion model for video generation
Bar-Tal, O., Chefer, H., Tov, O., Herrmann, C., Paiss, R., Zada, S., Ephrat, A., Hur, J., Li, Y., Michaeli, T., et al · 2024
Closest in time.
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Cited alongside, same era.
Videocrafter1: Open diffusion models for high-quality video generation
Chen, H., Xia, M., He, Y., Zhang, Y., Cun, X., Yang, S., Xing, J., Liu, Y., Chen, Q., Wang, X., et al · 2023
Cited alongside, same era.
Dreamoving: A human video generation framework based on diffusion models, 2023
Feng, M., Liu, J., Yu, K., Yao, Y., Hui, Z., Guo, X., Lin, X., Xue, H., Shi, C., Li, X., et al · 2023
Cited alongside, same era.
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
Cited alongside, same era.
Scalable diffusion models with transformers
Peebles, W. and Xie, S · 2023
Cited alongside, same era.
Disco: Disentangled control for realistic human dance generation
Wang, T., Li, L., Lin, K., Zhai, Y., Lin, C.-C., Yang, Z., Zhang, H., Liu, Z., and Wang, L · 2023
Cited alongside, same era.
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
Cited alongside, same era.
Effective whole-body pose estimation with two-stages distillation
Yang, Z., Zeng, A., Yuan, C., and Li, Y · 2023
Cited alongside, same era.
Videocrafter2: Overcoming data limitations for high-quality video diffusion models
Chen, H., Zhang, Y., Cun, X., Xia, M., Wang, X., Weng, C., and Shan, Y · 2024
Closest in time.
Animate anyone: Consistent and controllable image-to-video synthesis for character animation
Hu, L · 2024
Closest in time.
Dispose: Disentangling pose guidance for controllable human image animation
Li, H., Li, Y., Yang, Y., Cao, J., Zhu, Z., Cheng, X., and Long, C · 2024
Closest in time.
Controlnext: Powerful and efficient control for image and video generation
Peng, B., Wang, J., Zhang, Y., Li, W., Yang, M.-C., and Jia, J · 2024
Closest in time.
Stableanimator: High-quality identity-preserving human image animation
Tu, S., Xing, Z., Han, X., Cheng, Z.-Q., Dai, Q., Luo, C., and Wu, Z · 2024
Closest in time.
Musev: Infinite-length and high fidelity virtual human video generation with visual conditioned parallel denoising
Xia, Z., Chen, Z., Wu, B., Li, C., Hung, K.-W., Zhan, C., He, Y., and Zhou, W · 2024
Closest in time.
Magicanimate: Temporally consistent human image animation using diffusion model
Xu, Z., Zhang, J., Liew, J. H., Yan, H., Liu, J.-W., Zhang, C., Feng, J., and Shou, M. Z · 2024
Closest in time.
Non-uniform timestep sampling: Towards faster diffusion model training
Zheng, T., Geng, C., Jiang, P., Wan, B., Zhang, H., Chen, J., Wang, J., and Li, B · 2024
Closest in time.
Beta-tuned timestep diffusion model
Zheng, T., Jiang, P., Wan, B., Zhang, H., Chen, J., Wang, J., and Li, B · 2024
Closest in time.