mlsanityData to 7 Oct 2026

Image Super-Resolution With Deep Variational Autoencoders

arXiv 2203.09445 ↗First posted 17 Mar 2022cs.CV cs.LG eess.IVcited by 11

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Abstract (arXiv)

Image super-resolution (SR) techniques are used to generate a high-resolution image from a low-resolution image. Until now, deep generative models such as autoregressive models and Generative Adversarial Networks (GANs) have proven to be effective at modelling high-resolution images. VAE-based models have often been criticised for their feeble generative performance, but with new advancements such as VDVAE, there is now strong evidence that deep VAEs have the potential to outperform current state-of-the-art models for high-resolution image generation. In this paper, we introduce VDVAE-SR, a new model that aims to exploit the most recent deep VAE methodologies to improve upon the results of similar models. VDVAE-SR tackles image super-resolution using transfer learning on pretrained VDVAEs. The presented model is competitive with other state-of-the-art models, having comparable results on image quality metrics.

Key facts. Cited by 11 papers in the map (data through 7 Oct 2026). Builds on 32 of its 47 references that are in the map. First posted on arXiv 17 Mar 2022.

Builds on

32 of 47 references.

References · 32

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20 more
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Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 3; 2023: 1; 2024: 4; 2025: 2; 2026: 1.

11 papers.

  1. 2024MTKD: Multi-Teacher Knowledge Distillation for Image Super-Resolutioncited by 17
  2. 2022Generative Adversarial Networks for Image Super-Resolution: A Surveycited by 11
  3. 2024TwinDiffusion: Enhancing Coherence and Efficiency in Panoramic Image Generation with Diffusion Modelscited by 5
  4. 2024Survey on Visual Signal Coding and Processing with Generative Models: Technologies, Standards and Optimizationcited by 2
  5. 2022High-Resolution CMB Lensing Reconstruction with Deep Learningcited by 0
  6. 2022Diverse super-resolution with pretrained deep hiererarchical VAEscited by 0
  7. 2023From Unimodal to Multimodal: improving sEMG-Based Pattern Recognition via deep generative modelscited by 0
  8. 2024Quantifying Climate Change Impacts on Renewable Energy Generation: A Super-Resolution Recurrent Diffusion Modelcited by 0
  9. 2025Appeal prediction for AI up-scaled Imagescited by 0
  10. 2025Masked Conditioning for Deep Generative Modelscited by 0
  11. 2026SyMTRS: Benchmark Multi-Task Synthetic Dataset for Depth, Domain Adaptation and Super-Resolution in Aerial Imagerycited by 0