mlsanityData to 14 Oct 2026

Under-Display Camera Image Restoration with Scattering Effect

arXiv 2308.04163 ↗First posted 8 Aug 2023cs.CV eess.IVcited by 12

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Abstract (arXiv)

The under-display camera (UDC) provides consumers with a full-screen visual experience without any obstruction due to notches or punched holes. However, the semi-transparent nature of the display inevitably introduces the severe degradation into UDC images. In this work, we address the UDC image restoration problem with the specific consideration of the scattering effect caused by the display. We explicitly model the scattering effect by treating the display as a piece of homogeneous scattering medium. With the physical model of the scattering effect, we improve the image formation pipeline for the image synthesis to construct a realistic UDC dataset with ground truths. To suppress the scattering effect for the eventual UDC image recovery, a two-branch restoration network is designed. More specifically, the scattering branch leverages global modeling capabilities of the channel-wise self-attention to estimate parameters of the scattering effect from degraded images. While the image branch exploits the local representation advantage of CNN to recover clear scenes, implicitly guided by the scattering branch. Extensive experiments are conducted on both real-world and synthesized data, demonstrating the superiority of the proposed method over the state-of-the-art UDC restoration techniques. The source code and dataset are available at urlhttps://github.com/NamecantbeNULL/SRUDC.

Key facts. Cited by 12 papers in the map (data through 14 Oct 2026). Builds on 25 of its 45 references that are in the map. First posted on arXiv 8 Aug 2023.

Builds on

25 of 45 references.

References · 25

  1. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,713
  2. 2018The Unreasonable Effectiveness of Deep Features as a Perceptual Metriccited by 11,177
  3. 2016SGDR: Stochastic Gradient Descent with Warm Restartscited by 5,045
  4. 2021Restormer: Efficient Transformer for High-Resolution Image Restorationcited by 1,627
  5. 2018Image Super-Resolution Using Very Deep Residual Channel Attention Networkscited by 1,264
  6. 2021Multi-Stage Progressive Image Restorationcited by 816
  7. 2022Simple Baselines for Image Restorationcited by 708
  8. 2017Benchmarking Single Image Dehazing and Beyondcited by 447
  9. 2019Selective Kernel Networkscited by 403
  10. 2018Recovering Realistic Texture in Image Super-resolution by Deep Spatial Feature Transformcited by 371
  11. 2022MAXIM: Multi-Axis MLP for Image Processingcited by 302
  12. 2021Underwater Image Enhancement via Medium Transmission-Guided Multi-Color Space Embeddingcited by 134
13 more
  1. 2021Channel-Wise Attention-Based Network for Self-Supervised Monocular Depth Estimationcited by 63
  2. 2021HDRUNet: Single Image HDR Reconstruction with Denoising and Dequantizationcited by 58
  3. 2020Image Restoration for Under-Display Cameracited by 47
  4. 2021Removing Diffraction Image Artifacts in Under-Display Camera via Dynamic Skip Connection Networkcited by 31
  5. 2021A New Journey from SDRTV to HDRTVcited by 30
  6. 2023Generating Aligned Pseudo-Supervision from Non-Aligned Data for Image Restoration in Under-Display Cameracited by 16
  7. 2022MIPI 2022 Challenge on Under-Display Camera Image Restoration: Methods and Resultscited by 14
  8. 2022Rethinking Performance Gains in Image Dehazing Networkscited by 12
  9. 2020Transform Domain Pyramidal Dilated Convolution Networks For Restoration of Under Display Camera Imagescited by 11
  10. 2022UDC-UNet: Under-Display Camera Image Restoration via U-Shape Dynamic Networkcited by 11
  11. 2020Deep Atrous Guided Filter for Image Restoration in Under Display Camerascited by 10
  12. 2022Modular Degradation Simulation and Restoration for Under-Display Cameracited by 7
  13. 2022Real-Time Under-Display Cameras Image Restoration and HDR on Mobile Devicescited by 5

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 7; 2025: 4; 2026: 1.

12 papers.