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Generative models have enabled the creation of contents that are indistinguishable from those taken from nature.
Image quality assessment: from error visibility to structural similarity
Wang, Z., Bovik, A., Sheikh, H., and Simoncelli, E · 2003
Earlier work this paper cites.
Invertible conditional gans for image editing
Perarnau, G., Van De Weijer, J., Raducanu, B., and Álvarez, J. M · 2016
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Improved techniques for training gans
Salimans, T., Goodfellow, I., Zaremba, W., Cheung, V., Radford, A., and Chen, X · 2016
Earlier work this paper cites.
Gans trained by a two time-scale update rule converge to a local nash equilibrium
Heusel, M., Ramsauer, H., Unterthiner, T., Nessler, B., and Hochreiter, S · 2017
Earlier work this paper cites.
Attributing fake images to gans: Analyzing fingerprints in generated images
Yu, N., Davis, L., and Fritz, M · 2018
Earlier work this paper cites.
The unreasonable effectiveness of deep features as a perceptual metric
Zhang, R., Isola, P., Efros, A. A., Shechtman, E., and Wang, O · 2018
Earlier work this paper cites.
Image2stylegan: How to embed images into the stylegan latent space?
Abdal, R., Qin, Y., and Wonka, P · 2019
Earlier work this paper cites.
Inverting layers of a large generator
Bau, D., Zhu, J.-Y., Wulff, J., Peebles, W., Strobelt, H., Zhou, B., and Torralba, A · 2019
Earlier work this paper cites.
The bizarre and terrifying case of the “deepfake” video that helped bring an african nation to the brink
Breland, A · 2019
Earlier work this paper cites.
A style-based generator architecture for generative adversarial networks
Karras, T., Laine, S., and Aila, T · 2019
Cited alongside, same era.
Language models are unsupervised multitask learners
Radford, A., Wu, J., Child, R., Luan, D., Amodei, D., and Sutskever, I · 2019
Cited alongside, same era.
Experts: Spy used ai-generated face to connect with targets
Satter, R · 2019
Cited alongside, same era.
Openai api, 2020
Brockman, G., Murati, M., Welinder, P., and OpenAI · 2020
Cited alongside, same era.
Stargan v2: Diverse image synthesis for multiple domains
Choi, Y., Uh, Y., Yoo, J., and Ha, J.-W · 2020
Cited alongside, same era.
Ganspace: Discovering interpretable gan controls
Härkönen, E., Hertzmann, A., Lehtinen, J., and Paris, S · 2020
Cited alongside, same era.
Decentralized attribution of generative models
Kim, C., Ren, Y., and Yang, Y · 2021
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Zero-shot text-to-image generation
Ramesh, A., Pavlov, M., Goh, G., Gray, S., Voss, C., Radford, A., Chen, M., and Sutskever, I · 2021
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Low-rank subspaces in gans
Zhu, J., Feng, R., Shen, Y., Zhao, D., Zha, Z.-J., Zhou, J., and Chen, Q · 2021
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Multi-instrument music synthesis with spectrogram diffusion
Hawthorne, C., Simon, I., Roberts, A., Zeghidour, N., Gardner, J., Manilow, E., and Engel, J · 2022
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Dall·e 2 preview - risks and limitations, 2022
Mishkin, P. and Ahmad, L · 2022
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Hierarchical text-conditional image generation with clip latents
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Transforming and projecting images into class-conditional generative networks
Huh, M., Zhang, R., Zhu, J.-Y., Paris, S., and Hertzmann, A · 2020
Cited alongside, same era.
Analyzing and improving the image quality of stylegan
Karras, T., Laine, S., Aittala, M., Hellsten, J., Lehtinen, J., and Aila, T · 2020
Cited alongside, same era.
Responsible disclosure of generative models using scalable fingerprinting
Yu, N., Skripniuk, V., Chen, D., Davis, L., and Fritz, M · 2020
Cited alongside, same era.
Ramesh, A., Dhariwal, P., Nichol, A., Chu, C., and Chen, M · 2022
Later among the works it cites.
High-resolution image synthesis with latent diffusion models
Rombach, R., Blattmann, A., Lorenz, D., Esser, P., and Ommer, B · 2022
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Gan inversion: A survey
Xia, W., Zhang, Y., Yang, Y., Xue, J.-H., Zhou, B., and Yang, M.-H · 2022
Later among the works it cites.