Explicit Diffusion of Gaussian Mixture Model Based Image Priors
In this work we tackle the problem of estimating the density $f_X$ of a random variable $X$ by successive smoothing, such that the smoothed random variable $Y$ fulfills $(\partial_t - \Delta_1)f_Y(\,\cdot\,, t) = 0$, $f_Y(\,\cdot\,, 0) = f_X$. With a focus on image processing, we propose a product/fields of experts model with Gaussian mixture experts that admits an analytic expression for $f_Y (\,\cdot\,, t)$ under an orthogonality constraint on the filters. This construction naturally allows the model to be trained simultaneously over the entire diffusion horizon using empirical Bayes. We show preliminary results on image denoising where our model leads to competitive results while being tractable, interpretable, and having only a small number of learnable parameters. As a byproduct, our model can be used for reliable noise estimation, allowing blind denoising of images corrupted by heteroscedastic noise.
Code (0)
등록된 구현이 없습니다.
Tasks
DenoisingImage DenoisingNoise EstimationMethods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
Integrating Reweighted Least Squares with Plug-and-Play Diffusion Priors for Noisy Image Restoration
Existing plug-and-play image restoration methods typically employ off-the-shelf Gaussian denoisers as proximal operators within classical optimization frameworks based on variable splitting. Recently, denoisers induced b…
Image RestorationDSplats: 3D Generation by Denoising Splats-Based Multiview Diffusion Models
Generating high-quality 3D content requires models capable of learning robust distributions of complex scenes and the real-world objects within them. Recent Gaussian-based 3D reconstruction techniques have achieved impre…
3D Generation3D ReconstructionDenoisingImage to 3D+2Score Priors Guided Deep Variational Inference for Unsupervised Real-World Single Image Denoising
Real-world single image denoising is crucial and practical in computer vision. Bayesian inversions combined with score priors now have proven effective for single image denoising but are limited to white Gaussian noise. …
DenoisingImage DenoisingVariational InferenceHuman-3Diffusion: Realistic Avatar Creation via Explicit 3D Consistent Diffusion Models
Creating realistic avatars from a single RGB image is an attractive yet challenging problem. Due to its ill-posed nature, recent works leverage powerful prior from 2D diffusion models pretrained on large datasets. Althou…
3D ReconstructionProduct of Gaussian Mixture Diffusion Model for non-linear MRI Inversion
Diffusion models have recently shown remarkable results in magnetic resonance imaging reconstruction. However, the employed networks typically are black-box estimators of the (smoothed) prior score with tens of millions …