Using Hidden Feature Space of Diffusion Neural Networks for Image Blending Problem
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Publisher
Pleiades Publishing Ltd
Link
https://link.springer.com/content/pdf/10.1134/S1063779624030468.pdf
Reference9 articles.
1. D. Xing and A. Tzes, “Synthetic aerial dataset for UAV detection via text-to-image diffusion models,” in Proceedings of IEEE Conference on Artificial Intelligence (CAI), Santa Clara, CA, USA, 2023. https://doi.org/10.1109/CAI54212.2023.00030
2. A. Nair and N. Mehendale, “Dronescape: A high-resolution drone footage dataset for tree region segmentation.” https://ssrn.com/abstract=4512595. Accessed July 17, 2023.https://doi.org/10.2139/ssrn.4512595
3. R. Rombach, A. Blattmann, D. Lorenz, P. Esser, and B. Ommer, “High-resolution image synthesis with latent diffusion models,” (2022). https://doi.org/10.48550/arXiv.2112.10752
4. A. Lugmayr, M. Danelljan, A. Romero, F. Yu, R. Timofte, and L. Van Gool, “Repaint: Inpainting using denoising diffusion probabilistic models,” (2022). arXiv:2201.09865.
5. L. Zhang and M. Agrawala, “Adding conditional control to text-to-image diffusion models,” (2023). arXiv: 2302.05543.
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