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awesome-lf-image-sr's Introduction

With recent advances in camera manufacturing, light field (LF) imaging technology becomes increasingly popular and is commonly used in various applications such as mobile phones, biological microscope, VR/AR etc. Since both intensity and directions of light rays are recorded by LF cameras, the resolution of LF images can be enhanced by using these additional angular information. LF image super-resolution (SR), also known as LF spatial SR, aims at reconstructing high-resolution (HR) LF images from their low-resolution (LR) conterparts. In this repository, we present a collection of papers and datasets on LF image SR, together with their codes and repos.

Note: This repository will be updated on a regular basis, so stay tuned~~๐ŸŽ‰๐ŸŽ‰๐ŸŽ‰

Datasets

A more comprehensive overview of LF datasets can be viewed through this link. Here, we only list several popular datasets which are commonly used for LF image SR:

  • New light field image dataset (EPFL). website; paper
  • Datasets and Benchmarks for Densely Sampled 4D Light Fields (HCIold). paper
  • 4D Light Field Dataset (HCInew). website; paper
  • INRIA Light field dataset (INRIA). website; paper
  • The (New) Stanford Light Field Archive (STFgantry). website
  • Stanford Lytro Light Field Archive (STFLytro). website

Methods

Model Published Codes Keywords Better Performance than
Bishop et al. TPAMI2012 -- pioneering work, variational Bayesian, Lambertian prior --
GMM CVPRW2012 -- pioneering work, Gaussian mixture model, subspace projection --
Wanner et al. ECCV2012 & TPAMI2013 -- pioneering work, structure tensor, variational framework --
LFCNN ICCVW2015 & SPL2017 TensorFlow first CNN-based method GMM, Wanner et al.
PCA_rr JSTSP2017 Matlab PCA, ridge regression, patch matching LFCNN, SRCNN, ANR, NCSR
LFSR_Gul TIP2018 -- CNN LFCNN, DRRN
GB MMSP2017 & TIP2018 Matlab graph-based regularization Wanner et al., GMM, SRCNN
LFNet TIP2018 Theano bidirectional recurrent CNN LFCNN, FSRCNN, VDSR, BRCN, DRRN
LRP TPAMI2018 -- low-rank prior, SVD, QR decomposition, CNN LFCNN, PCA_rr, VDSR
LFBM5D ICIP2018 Matlab/C++ entend SR-BM3D to LFs PCA_rr, SR-BM3D
LF-DCNN SPL2018 -- EDSR + EPI enhancement LFCNN, GB, EDSR
LFSSR TIP2018 MatConvNet spatial-angular separable convolution LFCNN, PCA_rr, GB, VDSR, LapSRN
MCSTF IJCV2019 -- motion-compensated spatio-temporal filtering LFBM5D, GB, SRCNN, VSR, DeepSR, SPMC
EPGB TMM2019 -- edge-preserved graph-based regularization GMM, LFNet, GB, SRCNN
LF-FusNet ICIP2017 & TCSVT2019 Caffe internal and external similarity PCA_rr, LFNet, GB, VDSR
resLF CVPR2019 PyTorch multi-branch inputs, residual blocks GMM, Wanner et al., LFCNN, LFNet, GB, EDSR
Zhu et al. CVPRW2019 TensorFlow epipolar volume autoencoder, adversarial loss GB, SRGAN
HDDRNet TPAMI2019 & AAAI2020 TensorFlow 4D convolution, dense residual connection LFCNN, PCA_rr, LFNet, resLF, VDSR, MSLapSRN, RDN, ESPCN, DUF
Jin et al. CVPR2020 -- combinatorial geometry embedding, structural consistency regularization PCA_rr, LFNet, GB, resLF, EDSR
LF-InterNet arXiv2020 PyTorch spatial-angular interaction LFBM5D, GB, LFNet, LFSSR, resLF, VDSR, EDSR, RCAN, SAN, SRGAN, ESRGAN

Acknowledgement

We would like to thank Zhen Cheng for the helpful discussion and insightful advice regarding this work.

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