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Denoising diffusion models have emerged as a powerful tool for various image generation and editing tasks, facilitating the synthesis of visual content in an unconditional or input-conditional manner.
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2023
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F. P. Papantoniou, A. Lattas, S. Moschoglou, and S. Zafeiriou, “Relightify: Relightable 3d faces from a single image via diffusion models,” in
2023
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2023
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2023
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J. Xiang, J. Yang, B. Huang, and X. Tong, “3d-aware image generation using 2d diffusion models,”
2023
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2023
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K. Kotar, S. Tian, H.-X. Yu, D. Yamins, and J. Wu, “Are these the same apple? comparing images based on object intrinsics,” in
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2024
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Y. Huang, J. Huang, J. Liu, Y. Dong, J. Lv, and S. Chen, “Wavedm: Wavelet-based diffusion models for image restoration,”
2024
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H. Cao, C. Tan, Z. Gao, Y. Xu, G. Chen, P.-A. Heng, and S. Z. Li, “A survey on generative diffusion models,”
2024
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X. Xu, J. Guo, Z. Wang, G. Huang, I. Essa, and H. Shi, “Prompt-free diffusion: Taking” text” out of text-to-image diffusion models,” in
2024
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Y. Gu, X. Wang, J. Z. Wu, Y. Shi, Y. Chen, Z. Fan, W. Xiao, R. Zhao, S. Chang, W. Wu,
2024
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N. Ruiz, Y. Li, V. Jampani, W. Wei, T. Hou, Y. Pritch, N. Wadhwa, M. Rubinstein, and K. Aberman, “Hyperdreambooth: Hypernetworks for fast personalization of text-to-image models,” in
2024
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2024
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Z. Zhao, Y. Chen, Z. Hu, X. Chen, and B. Ni, “Vector graphics generation via mutually impulsed dual-domain diffusion,” in
2024
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2024
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T. Islam, A. Miron, X. Liu, and Y. Li, “Deep learning in virtual try-on: A comprehensive survey,”
2024
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J. Kim, G. Gu, M. Park, S. Park, and J. Choo, “Stableviton: Learning semantic correspondence with latent diffusion model for virtual try-on,” in
2024
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2024
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2024
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N. Huang, Y. Zhang, F. Tang, C. Ma, H. Huang, W. Dong, and C. Xu, “Diffstyler: Controllable dual diffusion for text-driven image stylization,”
2024
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Z. Lu, C. Wu, X. Chen, Y. Wang, L. Bai, Y. Qiao, and X. Liu, “Hierarchical diffusion autoencoders and disentangled image manipulation,” in
2024
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Z. Zhang, J. Zheng, Z. Fang, and B. A. Plummer, “Text-to-image editing by image information removal,” in
2024
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K. Joseph, P. Udhayanan, T. Shukla, A. Agarwal, S. Karanam, K. Goswami, and B. V. Srinivasan, “Iterative multi-granular image editing using diffusion models,” in
2024
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L. Han, S. Wen, Q. Chen, Z. Zhang, K. Song, M. Ren, R. Gao, A. Stathopoulos, X. He, Y. Chen,
2024
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J. Jeong, M. Kwon, and Y. Uh, “Training-free content injection using h-space in diffusion models,” in
2024
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D. H. Park, G. Luo, C. Toste, S. Azadi, X. Liu, M. Karalashvili, A. Rohrbach, and T. Darrell, “Shape-guided diffusion with inside-outside attention,” in
2024
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V. Sarukkai, L. Li, A. Ma, C. Ré, and K. Fatahalian, “Collage diffusion,” in
2024
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Y. Song, Z. Zhang, Z. Lin, S. Cohen, B. Price, J. Zhang, S. Y. Kim, H. Zhang, W. Xiong, and D. Aliaga, “Imprint: Generative object compositing by learning identity-preserving representation,” in
2024
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Y. Wang, W. Zhang, J. Zheng, and C. Jin, “Primecomposer: Faster progressively combined diffusion for image composition with attention steering,”
2024
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J. Xu, S. Motamed, P. Vaddamanu, C. H. Wu, C. Haene, J.-C. Bazin, and F. De la Torre, “Personalized face inpainting with diffusion models by parallel visual attention,” in
2024
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C. Zeng, Y. Dong, P. Peers, Y. Kong, H. Wu, and X. Tong, “Dilightnet: Fine-grained lighting control for diffusion-based image generation,” in
2024
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P. Kocsis, J. Philip, K. Sunkavalli, M. Nießner, and Y. Hold-Geoffroy, “Lightit: Illumination modeling and control for diffusion models,” in
2024
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2024
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2024
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S. Sheynin, A. Polyak, U. Singer, Y. Kirstain, A. Zohar, O. Ashual, D. Parikh, and Y. Taigman, “Emu edit: Precise image editing via recognition and generation tasks,” in
2024
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