mlsanityData to 7 Oct 2026

Compound Multi-branch Feature Fusion for Real Image Restoration

arXiv 2206.02748 ↗First posted 2 Jun 2022eess.IV cs.CV cs.LGcited by 2

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Abstract (arXiv)

Image restoration is a challenging and ill-posed problem which also has been a long-standing issue. However, most of learning based restoration methods are proposed to target one degradation type which means they are lack of generalization. In this paper, we proposed a multi-branch restoration model inspired from the Human Visual System (i.e., Retinal Ganglion Cells) which can achieve multiple restoration tasks in a general framework. The experiments show that the proposed multi-branch architecture, called CMFNet, has competitive performance results on four datasets, including image dehazing, deraindrop, and deblurring, which are very common applications for autonomous cars. The source code and pretrained models of three restoration tasks are available at https://github.com/FanChiMao/CMFNet.

Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 42 of its 62 references that are in the map. First posted on arXiv 2 Jun 2022.

Builds on

42 of 62 references.

References · 42

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30 more
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Cited by year

Citing papers per year: 2023: 2.

2 papers.

  1. 2023Memory augment is All You Need for image restorationcited by 8
  2. 2023Joint Depth Estimation and Mixture of Rain Removal From a Single Imagecited by 0