arXiv:2505.12375
공식 코드 · Papers with Code
Trustworthy Image Super-Resolution via Generative Pseudoinverse
원문 초록
We consider the problem of trustworthy image restoration, taking the form of a constrained optimization over the prior density. To this end, we develop generative models for the task of image super-resolution that respect the degradation process and that can be made asymptotically consistent with the low-resolution measurements, outperforming existing methods by a large margin in that respect.
함께 살펴볼 논문
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GuideSR: Rethinking Guidance for One-Step High-Fidelity Diffusion-Based Super-Resolution
IM-LUT: Interpolation Mixing Look-Up Tables for Image Super-Resolution
EAMamba: Efficient All-Around Vision State Space Model for Image Restoration
Unsupervised Imaging Inverse Problems with Diffusion Distribution Matching
Structural Similarity-Inspired Unfolding for Lightweight Image Super-Resolution
DACN: Dual-Attention Convolutional Network for Hyperspectral Image Super-Resolution
토론
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