mlsanityData to 7 Oct 2026

Steered Mixture of Experts Regression for Image Denoising with Multi-Model-Inference

arXiv 2303.17409 ↗First posted 30 Mar 2023eess.IVcited by 4

On the map: Mixture-of-experts → Vision mixture-of-experts

Abstract (arXiv)

In this paper we introduce a novel block-based regression strategy for image denoising based on edge-aware Steered-Mixture-of-Experts (SMoE) models. SMoEs provide very sparse image representations, able to model sharp edges as well as smooth transitions in images efficiently with few parameters. A multi-model inference strategy is developed that improves significantly the denoising capacity of single SMoE models. We show that the important edge reconstruction properties of SMoEs are well preserved, even when many models are fused under severe noise. We investigate model-inference from local neighborhood blocks as well as from distant blocks using block-matching as in BM3D. Our initial results indicate that SMoE multi-model regression can provide promising results compared to state-of-the-art BM3D with excellent edge quality.

Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). Placed in Vision mixture-of-experts, one of 12 directions in Mixture-of-experts. Builds on 4 of its 31 references that are in the map. First posted on arXiv 30 Mar 2023.

Builds on

4 of 31 references.

Closest ancestors · 1

Same direction, newest first

  1. 2022Edge-Aware Autoencoder Design for Real-Time Mixture-of-Experts Image Compression25 Jul

Other references · 3

  1. 2019Deep Learning on Image Denoising: An overviewcited by 128
  2. 2020NTIRE 2020 Challenge on Real Image Denoising: Dataset, Methods and Resultscited by 51
  3. 2019New Risk Bounds for 2D Total Variation Denoisingcited by 6

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Cited by year

Citing papers per year: 2023: 1; 2024: 2; 2025: 1.

4 papers.

  1. 2023Steered Mixture-of-Experts Autoencoder Design for Real-Time Image Modelling and Denoisingcited by 5
  2. 2024Adaptive Segmentation-Based Initialization for Steered Mixture of Experts Image Regressioncited by 3
  3. 2024Denoising OCT Images Using Steered Mixture of Experts with Multi-Model Inferencecited by 0
  4. 2025Rasterized Steered Mixture of Experts for Efficient 2D Image Regressioncited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2026Edge-Aligned Initialization of Kernels for Steered Mixture-of-Experts
  2. 2023Soft Mixture Denoising: Beyond the Expressive Bottleneck of Diffusion Models
  3. 2022Sparse Video Representation Using Steered Mixture-of-Experts With Global Motion Compensation
  4. 2023Learning Gradually Non-convex Image Priors Using Score Matching
  5. 2025Sparse Mixture-of-Experts for Non-Uniform Noise Reduction in MRI Images
  6. 2026Efficient and Training-Free Single-Image Diffusion Models
  7. 2023SUD2: Supervision by Denoising Diffusion Models for Image Reconstruction
  8. 2022Denoising Diffusion Restoration Models