mlsanityData to 7 Oct 2026

Hypernetwork-Based Adaptive Image Restoration

arXiv 2206.05970 ↗First posted 13 Jun 2022cs.CV eess.IVcited by 8

Not on the map. Why?

Abstract (arXiv)

Adaptive image restoration models can restore images with different degradation levels at inference time without the need to retrain the model. We present an approach that is highly accurate and allows a significant reduction in the number of parameters. In contrast to existing methods, our approach can restore images using a single fixed-size model, regardless of the number of degradation levels. On popular datasets, our approach yields state-of-the-art results in terms of size and accuracy for a variety of image restoration tasks, including denoising, deJPEG, and super-resolution.

Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). Builds on 13 of its 20 references that are in the map. First posted on arXiv 13 Jun 2022.

Builds on

13 of 20 references.

References · 13

  1. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  2. 2016Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Networkcited by 1,199
  3. 2016HyperNetworkscited by 1,003
  4. 2018Residual Dense Network for Image Restorationcited by 181
  5. 2019Meta-SR: A Magnification-Arbitrary Network for Super-Resolutioncited by 180
  6. 2015Compression Artifacts Reduction by a Deep Convolutional Networkcited by 136
  7. 2018Deep Network Interpolation for Continuous Imagery Effect Transitioncited by 47
  8. 2019Modulating Image Restoration with Continual Levels via Adaptive Feature Modification Layerscited by 39
  9. 2019CFSNet: Toward a Controllable Feature Space for Image Restorationcited by 25
  10. 2020MetaDistiller: Network Self-Boosting via Meta-Learned Top-Down Distillationcited by 18
  11. 2018Decouple Learning for Parameterized Image Operatorscited by 11
  12. 2018Dynamic-Net: Tuning the Objective Without Re-training for Synthesis Taskscited by 9
1 more
  1. 2020Smoother Network Tuning and Interpolation for Continuous-level Image Processingcited by 3

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 6; 2025: 1; 2026: 1.

8 papers.

  1. 2024HyperFusion: A Hypernetwork Approach to Multimodal Integration of Tabular and Medical Imaging Data for Predictive Modelingcited by 15
  2. 2024HAIR: Hypernetworks-based All-in-One Image Restorationcited by 12
  3. 2024Enhancing Diversity in Bayesian Deep Learning via Hyperspherical Energy Minimization of CKAcited by 2
  4. 2024GAURA: Generalizable Approach for Unified Restoration and Rendering of Arbitrary Viewscited by 1
  5. 2025HyDA: Hypernetworks for Test Time Domain Adaptation in Medical Imaging Analysiscited by 1
  6. 2024ChannelDropBack: Forward-Consistent Stochastic Regularization for Deep Networkscited by 0
  7. 2024SMM-Conv: Scalar Matrix Multiplication with Zero Packing for Accelerated Convolutioncited by 0
  8. 2026Patient-Conditioned Adaptive Offsets for Reliable Diagnosis across Subgroupscited by 0