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Diffusion distillation is a widely used technique to reduce the sampling cost of diffusion models, yet it often requires extensive training, and the student performance tends to be degraded.
Imagenet: A large-scale hierarchical image database
Deng, J., Dong, W., Socher, R., Li, L.-J., Li, K., and Fei-Fei, L · 2009
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Learning multiple layers of features from tiny images
Krizhevsky, A · 2009
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Generative adversarial networks, 2014
Goodfellow, I. J., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., Courville, A., and Bengio, Y · 2014
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Batch normalization: Accelerating deep network training by reducing internal covariate shift, 2015
Ioffe, S. and Szegedy, C · 2015
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Microsoft coco: Common objects in context, 2015
Lin, T.-Y., Maire, M., Belongie, S., Bourdev, L., Girshick, R., Hays, J., Perona, P., Ramanan, D., Zitnick, C. L., and Dollár, P · 2015
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Very deep convolutional networks for large-scale image recognition, 2015
Simonyan, K. and Zisserman, A · 2015
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Deep unsupervised learning using nonequilibrium thermodynamics, 2015
Sohl-Dickstein, J., Weiss, E. A., Maheswaranathan, N., and Ganguli, S · 2015
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Improved techniques for training gans, 2016
Salimans, T., Goodfellow, I., Zaremba, W., Cheung, V., Radford, A., and Chen, X · 2016
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Gans trained by a two time-scale update rule converge to a local nash equilibrium, 2018
Heusel, M., Ramsauer, H., Unterthiner, T., Nessler, B., and Hochreiter, S · 2018
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Which training methods for gans do actually converge?, 2018
Mescheder, L., Geiger, A., and Nowozin, S · 2018
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The unreasonable effectiveness of deep features as a perceptual metric, 2018
Zhang, R., Isola, P., Efros, A. A., Shechtman, E., and Wang, O · 2018
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Large scale gan training for high fidelity natural image synthesis, 2019
Brock, A., Donahue, J., and Simonyan, K · 2019
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A style-based generator architecture for generative adversarial networks, 2019
Karras, T., Laine, S., and Aila, T · 2019
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Improved precision and recall metric for assessing generative models, 2019
Kynkäänniemi, T., Karras, T., Laine, S., Lehtinen, J., and Aila, T · 2019
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Accelerating diffusion transformers with token-wise feature caching, 2024
Zou, C., Liu, X., Liu, T., Huang, S., and Zhang, L · 2019
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Stargan v2: Diverse image synthesis for multiple domains, 2020
Choi, Y., Uh, Y., Yoo, J., and Ha, J.-W · 2020
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Denoising diffusion probabilistic models, 2020
Ho, J., Jain, A., and Abbeel, P · 2020
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Efficientnet: Rethinking model scaling for convolutional neural networks, 2020
Tan, M. and Le, Q. V · 2020
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Differentiable augmentation for data-efficient gan training, 2020
Zhao, S., Liu, Z., Lin, J., Zhu, J.-Y., and Han, S · 2020
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Diffusion models beat gans on image synthesis, 2021
Dhariwal, P. and Nichol, A · 2021
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Taming transformers for high-resolution image synthesis, 2021
Esser, P., Rombach, R., and Ommer, B · 2021
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Score-based generative modeling through stochastic differential equations, 2021
Song, Y., Sohl-Dickstein, J., Kingma, D. P., Kumar, A., Ermon, S., and Poole, B · 2021
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Training data-efficient image transformers & distillation through attention, 2021
Touvron, H., Cord, M., Douze, M., Massa, F., Sablayrolles, A., and Jégou, H · 2021
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Maskgit: Masked generative image transformer, 2022
Chang, H., Zhang, H., Jiang, L., Liu, C., and Freeman, W. T · 2022
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Classifier-free diffusion guidance, 2022
Ho, J. and Salimans, T · 2022
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Elucidating the design space of diffusion-based generative models, 2022
Karras, T., Aittala, M., Aila, T., and Laine, S · 2022
Cited alongside, same era.
Improved techniques for training consistency models
Song, Y. and Dhariwal, P · 2023
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Consistency models, 2023
Song, Y., Dhariwal, P., Chen, M., and Sutskever, I · 2023
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Attention is all you need, 2023
Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., Kaiser, L., and Polosukhin, I · 2023
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Frequency compensated diffusion model for real-scene dehazing, 2023
Wang, J., Wu, S., Xu, K., and Yuan, Z · 2023
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Ufogen: You forward once large scale text-to-image generation via diffusion gans, 2023
Xu, Y., Zhao, Y., Xiao, Z., and Hou, T · 2023
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Nichol, A., Dhariwal, P., Ramesh, A., Shyam, P., Mishkin, P., McGrew, B., Sutskever, I., and Chen, M · 2022
Cited alongside, same era.
Hierarchical text-conditional image generation with clip latents, 2022
Ramesh, A., Dhariwal, P., Nichol, A., Chu, C., and Chen, M · 2022
Cited alongside, same era.
Photorealistic text-to-image diffusion models with deep language understanding, 2022
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., and Norouzi, M · 2022
Cited alongside, same era.
Progressive distillation for fast sampling of diffusion models, 2022
Salimans, T. and Ho, J · 2022
Cited alongside, same era.
Stylegan-xl: Scaling stylegan to large diverse datasets, 2022
Sauer, A., Schwarz, K., and Geiger, A · 2022
Cited alongside, same era.
Denoising diffusion implicit models, 2022
Song, J., Meng, C., and Ermon, S · 2022
Cited alongside, same era.
Perspectives on diffusion, 2023
Dieleman, S · 2023
Cited alongside, same era.
One-step diffusion with distribution matching distillation, 2023
Yin, T., Gharbi, M., Zhang, R., Shechtman, E., Durand, F., Freeman, W. T., and Park, T · 2023
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Fast sampling of diffusion models via operator learning, 2023
Zheng, H., Nie, W., Vahdat, A., Azizzadenesheli, K., and Anandkumar, A · 2023
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Consistency models made easy, 2024
Geng, Z., Pokle, A., Luo, W., Lin, J., and Kolter, J. Z · 2024
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Plug-and-play diffusion distillation, 2024
Hsiao, Y.-T., Khodadadeh, S., Duarte, K., Lin, W.-A., Qu, H., Kwon, M., and Kalarot, R · 2024
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Fouriscale: A frequency perspective on training-free high-resolution image synthesis, 2024
Huang, L., Fang, R., Zhang, A., Song, G., Liu, S., Liu, Y., and Li, H · 2024
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Distilling diffusion models into conditional gans, 2024
Kang, M., Zhang, R., Barnes, C., Paris, S., Kwak, S., Park, J., Shechtman, E., Zhu, J.-Y., and Park, T · 2024
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Lee, S., Jung, S.-W., and Seo, H · 2024
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Sdxl-lightning: Progressive adversarial diffusion distillation, 2024
Lin, S., Wang, A., and Yang, X · 2024
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Fast high-resolution image synthesis with latent adversarial diffusion distillation, 2024
Sauer, A., Boesel, F., Dockhorn, T., Blattmann, A., Esser, P., and Rombach, R · 2024
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Multi-student diffusion distillation for better one-step generators, 2024
Song, Y., Lorraine, J., Nie, W., Kreis, K., and Lucas, J · 2024
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San: Inducing metrizability of gan with discriminative normalized linear layer, 2024
Takida, Y., Imaizumi, M., Shibuya, T., Lai, C.-H., Uesaka, T., Murata, N., and Mitsufuji, Y · 2024
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Accelerating diffusion sampling with optimized time steps, 2024
Xue, S., Liu, Z., Chen, F., Zhang, S., Hu, T., Xie, E., and Li, Z · 2024
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Improved distribution matching distillation for fast image synthesis, 2024
Yin, T., Gharbi, M., Park, T., Zhang, R., Shechtman, E., Durand, F., and Freeman, W. T · 2024
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Dynamic diffusion transformer, 2024
Zhao, W., Han, Y., Tang, J., Wang, K., Song, Y., Huang, G., Wang, F., and You, Y · 2024
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Simplifying, stabilizing and scaling continuous-time consistency models, 2025
Lu, C. and Song, Y · 2025
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