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Diffusion models have recently shown the ability to generate high-quality images.
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Kim, G., Kwon, T., Ye, J.C.: Diffusionclip: Text-guided diffusion models for robust image manipulation. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 2426–2435 (2022)
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Dhariwal, P., Nichol, A.: Diffusion models beat gans on image synthesis. Advances in Neural Information Processing Systems 34
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Huo, J., Jin, S., Li, W., Wu, J., Lai, Y.K., Shi, Y., Gao, Y.: Manifold alignment for semantically aligned style transfer. In: Proceedings of the IEEE/CVF International Conference on Computer Vision. pp. 14861–14869 (2021)
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Avrahami, O., Lischinski, D., Fried, O.: Blended diffusion for text-driven editing of natural images. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 18208–18218 (2022)
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