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Recent text-to-image generative models such as Stable Diffusion are extremely adept at mimicking and generating copyrighted content, raising concerns amongst artists that their unique styles may be improperly copied.
Oakes, Calebrisi, Sotomayor: Tufenkian import export ventures inc v. einstein moomjy inc (2003), https://caselaw.findlaw.com/court/us-2nd-circuit/1455682.html
2003
Earlier work this paper cites.
Goldstein, P.: Goldstein on Copyright, 3rd edition. Wolters Kluwer Legal & Regulatory U.S. (2014)
2014
Earlier work this paper cites.
Gatys, L.A., Ecker, A.S., Bethge, M.: Image style transfer using convolutional neural networks. In: Proceedings of the IEEE conference on computer vision and pattern recognition. pp. 2414–2423 (2016)
2016
Earlier work this paper cites.
2017
Earlier work this paper cites.
2021
Earlier work this paper cites.
Caron, M., Touvron, H., Misra, I., Jégou, H., Mairal, J., Bojanowski, P., Joulin, A.: Emerging properties in self-supervised vision transformers. In: Proceedings of the IEEE/CVF international conference on computer vision. pp. 9650–9660 (2021)
2021
Earlier work this paper cites.
Radford, A., Kim, J.W., Hallacy, C., Ramesh, A., Goh, G., Agarwal, S., Sastry, G., Askell, A., Mishkin, P., Clark, J., Krueger, G., Sutskever, I.: Learning transferable visual models from natural language supervision (2021)
2021
Earlier work this paper cites.
Rombach, R., Blattmann, A., Lorenz, D., Esser, P., Ommer, B.: High-resolution image synthesis with latent diffusion models (2021)
2021
Earlier work this paper cites.
Pizzi, E., Roy, S.D., Ravindra, S.N., Goyal, P., Douze, M.: A self-supervised descriptor for image copy detection (2022)
2022
Earlier work this paper cites.
Saharia, C., Chan, W., Saxena, S., Li, L., Whang, J., Denton, E., Ghasemipour, S.K.S., Ayan, B.K., Mahdavi, S.S., Lopes, R.G., Salimans, T., Ho, J., Fleet, D.J., Norouzi, M.: Photorealistic text-to-image diffusion models with deep language understanding (2022)
2022
Earlier work this paper cites.
Schuhmann, C., Beaumont, R., Vencu, R., Gordon, C., Wightman, R., Cherti, M., Coombes, T., Katta, A., Mullis, C., Wortsman, M., Schramowski, P., Kundurthy, S., Crowson, K., Schmidt, L., Kaczmarczyk, R., Jitsev, J.: Laion-5b: An open large-scale dataset for training next generation image-text models (2022)
2022
Earlier work this paper cites.
Schuhmann, C., Beaumont, R., Vencu, R., Gordon, C.W., Wightman, R., Cherti, M., Coombes, T., Katta, A., Mullis, C., Wortsman, M., Schramowski, P., Kundurthy, S.R., Crowson, K., Schmidt, L., Kaczmarczyk, R., Jitsev, J.: LAION-5b: An open large-scale dataset for training next generation image-text models. In: Thirty-sixth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (2022), https://openreview.net/forum?id=M3Y74vmsMcY
2022
Cited alongside, same era.
Somepalli, G., Singla, V., Goldblum, M., Geiping, J., Goldstein, T.: Diffusion art or digital forgery? investigating data replication in diffusion models (2022)
2022
Cited alongside, same era.
Deepfloyd (Apr 2023), https://github.com/deep-floyd/IF
2023
Cited alongside, same era.
Generative artificial intelligence and copyright law (Sep 2023), https://crsreports.congress.gov/product/pdf/LSB/LSB10922
2023
Cited alongside, same era.
Rezaei, K., Saberi, M., Moayeri, M., Feizi, S.: Prime: Prioritizing interpretability in failure mode extraction (2023)
2023
Later among the works it cites.
Shan, S., Cryan, J., Wenger, E., Zheng, H., Hanocka, R., Zhao, B.Y.: Glaze: Protecting artists from style mimicry by text-to-image models (2023)
2023
Later among the works it cites.
Somepalli, G., Singla, V., Goldblum, M., Geiping, J., Goldstein, T.: Understanding and mitigating copying in diffusion models. In: Oh, A., Neumann, T., Globerson, A., Saenko, K., Hardt, M., Levine, S. (eds.) Advances in Neural Information Processing Systems. vol. 36, pp. 47783–47803. Curran Associates, Inc. (2023), https://proceedings.neurips.cc/paper_files/paper/2023/file/9521b6e7f33e039e7d92e23f5e37bbf4-Paper-Conference.pdf
2023
Later among the works it cites.
Zhao, Z., Duan, J., Xu, K., Wang, C., Guo, R.Z.Z.D.Q., Hu, X.: Can protective perturbation safeguard personal data from being exploited by stable diffusion? (2023)
2023
Later among the works it cites.
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Basu, S., Zhao, N., Morariu, V., Feizi, S., Manjunatha, V.: Localizing and editing knowledge in text-to-image generative models (2023)
2023
Cited alongside, same era.
Carlini, N., Hayes, J., Nasr, M., Jagielski, M., Sehwag, V., Tramèr, F., Balle, B., Ippolito, D., Wallace, E.: Extracting training data from diffusion models (2023)
2023
Cited alongside, same era.
Cui, Y., Ren, J., Xu, H., He, P., Liu, H., Sun, L., Xing, Y., Tang, J.: Diffusionshield: A watermark for copyright protection against generative diffusion models (2023)
2023
Cited alongside, same era.
Gandikota, R., Orgad, H., Belinkov, Y., Materzyńska, J., Bau, D.: Unified concept editing in diffusion models (2023)
2023
Cited alongside, same era.
Huang, X., Huang, Y.J., Zhang, Y., Tian, W., Feng, R., Zhang, Y., Xie, Y., Li, Y., Zhang, L.: Open-set image tagging with multi-grained text supervision. arXiv e-prints pp. arXiv–2310 (2023)
2023
Cited alongside, same era.
Kumari, N., Zhang, B., Wang, S.Y., Shechtman, E., Zhang, R., Zhu, J.Y.: Ablating concepts in text-to-image diffusion models (2023)
2023
Cited alongside, same era.
Zheng, L., Chiang, W.L., Sheng, Y., Zhuang, S., Wu, Z., Zhuang, Y., Lin, Z., Li, Z., Li, D., Xing, E., Zhang, H., Gonzalez, J.E., Stoica, I.: Judging LLM-as-a-judge with MT-bench and chatbot arena. In: Thirty-seventh Conference on Neural Information Processing Systems Datasets and Benchmarks Track (2023), https://openreview.net/forum?id=uccHPGDlao
2023
Later among the works it cites.
Cui, Y., Ren, J., Lin, Y., Xu, H., He, P., Xing, Y., Fan, W., Liu, H., Tang, J.: FT-SHIELD: A watermark against unauthorized fine-tuning in text-to-image diffusion models (2024), https://openreview.net/forum?id=OQccFglTb5
2024
Closest in time.
Podell, D., English, Z., Lacey, K., Blattmann, A., Dockhorn, T., Müller, J., Penna, J., Rombach, R.: SDXL: Improving latent diffusion models for high-resolution image synthesis. In: The Twelfth International Conference on Learning Representations (2024), https://openreview.net/forum?id=di52zR8xgf
2024
Closest in time.
Ren, J., Xu, H., He, P., Cui, Y., Zeng, S., Zhang, J., Wen, H., Ding, J., Liu, H., Chang, Y., Tang, J.: Copyright protection in generative ai: A technical perspective (2024)
2024
Closest in time.
Wang, Z., Chen, C., Lyu, L., Metaxas, D.N., Ma, S.: DIAGNOSIS: Detecting unauthorized data usages in text-to-image diffusion models. In: The Twelfth International Conference on Learning Representations (2024), https://openreview.net/forum?id=f8S3aLm0Vp
2024
Closest in time.
Xue, H., Liang, C., Wu, X., Chen, Y.: Toward effective protection against diffusion based mimicry through score distillation (2024)
2024
Closest in time.