https://github.com/bchao1/awesome-light-field-processing
A curated list of light field synthesis and light field reconstruction papers.
Science Score: 23.0%
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○CITATION.cff file
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○codemeta.json file
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○Scientific vocabulary similarity
Low similarity (7.9%) to scientific vocabulary
Repository
A curated list of light field synthesis and light field reconstruction papers.
Basic Info
- Host: GitHub
- Owner: bchao1
- Default Branch: master
- Size: 4.88 KB
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Metadata Files
README.md
Awesome Light Field Processing
A curated list of light field processing works.
Light field processing here refers to (but is not limited to) the following types of works: - Light field reconstruction / synthesis - Light field spatial super resolution - Light field depth estimation - etc ...
Table of Contents
- Light field synthesis
- Light field spatial super-resolution
- Light field depth estimation
- Light field compression
Light field synthesis
Learning-based Methods
|Paper|Link|Conference/Journal|Code|Notes| |--|--|--|--|--| |Learning Fused Pixel and Feature-based View Reconstructions for Light Fields|Link|IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2020||| |High-dimensional Dense Residual Convolutional Neural Network for Light Field Reconstruction|Link|IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) 2019||| |4D Temporally Coherent Light Field Video|Link|IEEE International Conference on 3D Vision (3DV) 2017||| |Dense Light Field Reconstruction From Sparse Sampling Using Residual Network|Link|Asian Conference on Computer Vision (ACCV) 2018||| |End-to-end View Synthesis for Light Field Imaging with Pseudo 4DCNN|Link|IEEE European Conference on Computer Vision (ECCV) 2018||| |Fast Light Field Reconstruction With Deep Coarse-To-Fine Modeling of Spatial-Angular Clues|Link|IEEE European Conference on Computer Vision (ECCV) 2018||| |LGFAN: 4D Light Field Synthesis from a Single RGB Image|Link|ACM Transactions on Multimedia Computing, Communications, and Applications 2020||| |Learning to Synthesize a 4D RGBD Light Field from a Single Image|Link|IEEE International Conference on Computer Vision (ICCV) 2017||| |Light Field Reconstruction Using Deep Convolutional Network on EPI|Link|IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2017||| |Multi-parallax views synthesis for three- dimensional light-field display using unsupervised CNN|Link|Optics Express 2017||| |Local Light Field Fusion: Practical View Synthesis with Prescriptive Sampling Guidelines|Link|ACM SIGGRAPH 2019||| |Learning-Based View Synthesis for Light Field Cameras|Link|ACM SIGGRAPH Asia 2016|||
Traditional Methods
|Paper|Link|Conference/Journal|Code|Notes| |--|--|--|--|--| |Learning Sheared EPI Structure for Light Field Reconstruction|Link|IEEE Transactions on Image Processing (TIP) 2019||| |Fast: Flow-Assisted Shearlet Transform for Densely-Sampled Light Field Reconstruction|Link|IEEE International Conference on Image Processing (ICIP) 2019||| |Light Field Reconstruction Using Shearlet Transform|Link|IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) 2018||| |Light Field Reconstruction Using Sparsity in the Continuous Fourier Domain|Link|ACM Transactions on Graphics (ToG) 2014|||
Light field spatial super resolution
Light field depth estimation
|Paper|Link|Conference/Journal|Code|Notes| |--|--|--|--|--| |Unsupervised Monocular Depth Estimation From Light Field Image|Link|IEEE Transactions on Image Processing (TIP) 2020||| |Learning to Think Outside the Box: Wide-Baseline Light Field Depth Estimation with EPI-Shift|Link|IEEE International Conference on 3D Vision (3DV) 2019||| |Unsupervised Depth Estimation from Light Field Using a Convolutional Neural Network|Link|IEEE International Conference on 3D Vision (3DV) 2018|||
Owner
- Name: Brian Chao
- Login: bchao1
- Kind: user
- Location: Stanford, California
- Company: Stanford University
- Website: https://bchao1.github.io
- Twitter: BrianCChao
- Repositories: 14
- Profile: https://github.com/bchao1
Stanford Ph.D. student. Research in computational photography, displays, and computer graphics. Open source enthusiast.
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