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T1: Scaling Diffusion Probabilistic Fields to High-Resolution on Unified Visual Modalities., , and . CoRR, (2023)AIM 2019 Challenge on RAW to RGB Mapping: Methods and Results., , , , , , , , , and 24 other author(s). ICCV Workshops, page 3584-3590. IEEE, (2019)LTT-GAN: Looking Through Turbulence by Inverting GANs., and . IEEE J. Sel. Top. Signal Process., 17 (3): 587-598 (May 2023)MDCN: Multi-Scale Dense Cross Network for Image Super-Resolution., , , , and . IEEE Trans. Circuits Syst. Video Technol., 31 (7): 2547-2561 (2021)Deep Semantic Statistics Matching (D2SM) Denoising Network., , and . ECCV (7), volume 13667 of Lecture Notes in Computer Science, page 384-400. Springer, (2022)Bigger is not Always Better: Scaling Properties of Latent Diffusion Models., , , , , and . CoRR, (2024)Latent Feature-Guided Diffusion Models for Shadow Removal., , , , , and . WACV, page 4301-4310. IEEE, (2024)Multi-scale Residual Network for Image Super-Resolution., , , and . ECCV (8), volume 11212 of Lecture Notes in Computer Science, page 527-542. Springer, (2018)An Effective Single-Image Super-Resolution Model Using Squeeze-and-Excitation Networks., , , , and . ICONIP (6), volume 11306 of Lecture Notes in Computer Science, page 542-553. Springer, (2018)Bi-Noising Diffusion: Towards Conditional Diffusion Models with Generative Restoration Priors., , and . CoRR, (2022)