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Virtual try-on, which aims to seamlessly fit garments onto person images, has recently seen significant progress with diffusion-based models.
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Dong, H., Liang, X., Shen, X., Wang, B., Lai, H., Zhu, J., Hu, Z., Yin, J.: Towards multi-pose guided virtual try-on network. In: Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) (October 2019)
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Goodfellow, I., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., Courville, A., Bengio, Y.: Generative adversarial networks. Commun. ACM 63
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Raffel, C., Shazeer, N., Roberts, A., Lee, K., Narang, S., Matena, M., Zhou, Y., Li, W., Liu, P.J.: Exploring the limits of transfer learning with a unified text-to-text transformer. Journal of Machine Learning Research 21
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2021
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Choi, S., Park, S., Lee, M., Choo, J.: Viton-hd: High-resolution virtual try-on via misalignment-aware normalization. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). pp. 14131–14140 (June 2021)
2021
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2021
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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. In: Meila, M., Zhang, T. (eds.) Proceedings of the 38th International Conference on Machine Learning. Proceedings of Machine Learning Research, vol. 139, pp. 8748–8763. PMLR (18–24 Jul 2021), https://proceedings.mlr.press/v139/radford21a.html
2021
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Zhu, L., Yang, D., Zhu, T., Reda, F., Chan, W., Saharia, C., Norouzi, M., Kemelmacher-Shlizerman, I.: Tryondiffusion: A tale of two unets. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). pp. 4606–4615 (June 2023)
2023
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2024
Later among the works it cites.
2024
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Esser, P., Kulal, S., Blattmann, A., Entezari, R., Müller, J., Saini, H., Levi, Y., Lorenz, D., Sauer, A., Boesel, F., Podell, D., Dockhorn, T., English, Z., Rombach, R.: Scaling rectified flow transformers for high-resolution image synthesis. In: Forty-first International Conference on Machine Learning (2024), https://openreview.net/forum?id=FPnUhsQJ5B
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Rombach, R., Blattmann, A., Lorenz, D., Esser, P., Ommer, B.: High-resolution image synthesis with latent diffusion models. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). pp. 10684–10695 (June 2022)
2022
Cited alongside, same era.
Chen, C.Y., Chen, Y.C., Shuai, H.H., Cheng, W.H.: Size does matter: Size-aware virtual try-on via clothing-oriented transformation try-on network. In: Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV). pp. 7513–7522 (October 2023)
2023
Cited alongside, same era.
Gou, J., Sun, S., Zhang, J., Si, J., Qian, C., Zhang, L.: Taming the power of diffusion models for high-quality virtual try-on with appearance flow. In: Proceedings of the 31st ACM International Conference on Multimedia. p. 7599–7607. MM ’23, Association for Computing Machinery, New York, NY, USA (2023). https://doi.org/10.1145/3581783.3612255, https://doi.org/10.1145/3581783.3612255
2023
Cited alongside, same era.
Morelli, D., Baldrati, A., Cartella, G., Cornia, M., Bertini, M., Cucchiara, R.: Ladi-vton: Latent diffusion textual-inversion enhanced virtual try-on. In: Proceedings of the 31st ACM International Conference on Multimedia. p. 8580–8589. MM ’23, Association for Computing Machinery, New York, NY, USA (2023). https://doi.org/10.1145/3581783.3612137, https://doi.org/10.1145/3581783.3612137
2023
Cited alongside, same era.
Peebles, W., Xie, S.: Scalable diffusion models with transformers. In: Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV). pp. 4195–4205 (October 2023)
2023
Cited alongside, same era.
2023
Cited alongside, same era.
2023
Cited alongside, same era.
Yang, B., Gu, S., Zhang, B., Zhang, T., Chen, X., Sun, X., Chen, D., Wen, F.: Paint by example: Exemplar-based image editing with diffusion models. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). pp. 18381–18391 (June 2023)
2023
Cited alongside, same era.
2024
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Gao, B., Ren, J., Shen, F., Wei, M., Huang, Z.: Exploring warping-guided features via adaptive latent diffusion model for virtual try-on. In: 2024 IEEE International Conference on Multimedia and Expo (ICME). pp. 1–6. IEEE (2024)
2024
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2024
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Kim, J., Gu, G., Park, M., Park, S., Choo, J.: Stableviton: Learning semantic correspondence with latent diffusion model for virtual try-on. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). pp. 8176–8185 (June 2024)
2024
Later among the works it cites.
2024
Later among the works it cites.
2024
Later among the works it cites.
2024
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