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We tackle the common challenge of inter-concept visual confusion in compositional concept generation using text-guided diffusion models (TGDMs).
Lora: Low-rank adaptation of large language models
Hu, E. J., Shen, Y., Wallis, P., Allen-Zhu, Z., Li, Y., Wang, S., Wang, L., and Chen, W · 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
Earlier work this paper cites.
Laion-400m: Open dataset of clip-filtered 400 million image-text pairs
Schuhmann, C., Vencu, R., Beaumont, R., Kaczmarczyk, R., Mullis, C., Katta, A., Coombes, T., Jitsev, J., and Komatsuzaki, A · 2021
Earlier work this paper cites.
ediffi: Text-to-image diffusion models with an ensemble of expert denoisers
Balaji, Y., Nah, S., Huang, X., Vahdat, A., Song, J., Kreis, K., Aittala, M., Aila, T., Laine, S., Catanzaro, B., et al · 2022
Earlier work this paper cites.
Training-free structured diffusion guidance for compositional text-to-image synthesis
Feng, W., He, X., Fu, T.-J., Jampani, V., Akula, A., Narayana, P., Basu, S., Wang, X. E., and Wang, W. Y · 2022
Earlier work this paper cites.
An image is worth one word: Personalizing text-to-image generation using textual inversion
Gal, R., Alaluf, Y., Atzmon, Y., Patashnik, O., Bermano, A. H., Chechik, G., and Cohen-Or, D · 2022
Earlier work this paper cites.
Prompt-to-prompt image editing with cross attention control
Hertz, A., Mokady, R., Tenenbaum, J., Aberman, K., Pritch, Y., and Cohen-Or, D · 2022
Earlier work this paper cites.
Compositional visual generation with composable diffusion models
Liu, N., Li, S., Du, Y., Torralba, A., and Tenenbaum, J. B · 2022
Earlier work this paper cites.
High-resolution image synthesis with latent diffusion models
Rombach, R., Blattmann, A., Lorenz, D., Esser, P., and Ommer, B · 2022
Earlier work this paper cites.
A neural space-time representation for text-to-image personalization
Alaluf, Y., Richardson, E., Metzer, G., and Cohen-Or, D · 2023
Cited alongside, same era.
Attend-and-excite: Attention-based semantic guidance for text-to-image diffusion models
Chefer, H., Alaluf, Y., Vinker, Y., Wolf, L., and Cohen-Or, D · 2023
Cited alongside, same era.
Mix-of-show: Decentralized low-rank adaptation for multi-concept customization of diffusion models
Gu, Y., Wang, X., Wu, J. Z., Shi, Y., Chen, Y., Fan, Z., Xiao, W., Zhao, R., Chang, S., Wu, W., et al · 2023
Cited alongside, same era.
Composer: Creative and controllable image synthesis with composable conditions
Huang, L., Chen, D., Liu, Y., Shen, Y., Zhao, D., and Zhou, J · 2023
Cited alongside, same era.
Kirillov, A., Mintun, E., Ravi, N., Mao, H., Rolland, C., Gustafson, L., Xiao, T., Whitehead, S., Berg, A. C., Lo, W.-Y., et al · 2023
Orthogonal adaptation for modular customization of diffusion models
Po, R., Yang, G., Aberman, K., and Wetzstein, G · 2023
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Dreambooth: Fine tuning text-to-image diffusion models for subject-driven generation
Ruiz, N., Li, Y., Jampani, V., Pritch, Y., Rubinstein, M., and Aberman, K · 2023
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Low-rank adaptation for fast text-to-image diffusion fine-tuning, 2023
Ryu, S · 2023
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Key-locked rank one editing for text-to-image personalization
Tewel, Y., Gal, R., Chechik, G., and Atzmon, Y · 2023
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Anti-dreambooth: Protecting users from personalized text-to-image synthesis
Van Le, T., Phung, H., Nguyen, T. H., Dao, Q., Tran, N. N., and Tran, A · 2023
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Cited alongside, same era.
Multi-concept customization of text-to-image diffusion
Kumari, N., Zhang, B., Zhang, R., Shechtman, E., and Zhu, J.-Y · 2023
Cited alongside, same era.
Cones 2: Customizable image synthesis with multiple subjects
Liu, Z., Zhang, Y., Shen, Y., Zheng, K., Zhu, K., Feng, R., Liu, Y., Zhao, D., Zhou, J., and Cao, Y · 2023
Cited alongside, same era.
Mou, C., Wang, X., Xie, L., Zhang, J., Qi, Z., Shan, Y., and Qie, X · 2023
Cited alongside, same era.
Localizing object-level shape variations with text-to-image diffusion models
Patashnik, O., Garibi, D., Azuri, I., Averbuch-Elor, H., and Cohen-Or, D · 2023
Cited alongside, same era.
Divide & bind your attention for improved generative semantic nursing
Li, Y., Keuper, M., Zhang, D., and Khoreva, A
Cited in the paper.
Generate anything anywhere in any scene
Li, Y., Liu, H., Wen, Y., and Lee, Y. J
Cited in the paper.
Voynov, A., Chu, Q., Cohen-Or, D., and Aberman, K · 2023
Later among the works it cites.
Inserting anybody in diffusion models via celeb basis
Yuan, G., Cun, X., Zhang, Y., Li, M., Qi, C., Wang, X., Shan, Y., and Zheng, H · 2023
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Adding conditional control to text-to-image diffusion models
Zhang, L., Rao, A., and Agrawala, M · 2023
Later among the works it cites.