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Latent Diffusion Models (LDMs) enable a wide range of applications but raise ethical concerns regarding illegal utilization.
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2022
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2023
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P. Dhariwal and A. Nichol, “Diffusion models beat gans on image synthesis,” Advances in Neural Information Processing Systems , vol. 34, pp. 8780–8794, 2021
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2021
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P. Esser, R. Rombach, and B. Ommer, “Taming transformers for high-resolution image synthesis,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , 2021, pp. 12 873–12 883
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2021
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2022
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2022
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2023
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2023
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2023
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2023
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2023
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2023
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2023
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2023
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2023
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R. Mokady, A. Hertz, K. Aberman, Y. Pritch, and D. Cohen-Or, “Null-text inversion for editing real images using guided diffusion models,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , 2023, pp. 6038–6047
2023
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2024
Closest in time.
S. Hong, K. Lee, S. Y. Jeon, H. Bae, and S. Y. Chun, “On exact inversion of dpm-solvers,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , 2024, pp. 7069–7078
2024
Closest in time.