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Awesome Computational Imaging

Awesome Computational Imaging

Chapter01_SIREN

From Paper to Code: Understanding and Reproducing “Implicit Neural Representations with Periodic Activation Functions”

Chapter02_NeRF

From Paper to Code: Understanding and Reproducing “NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis”

Chapter03_FourierFeatures

From Paper to Code: Understanding and Reproducing “Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains”

Chapter04_3D_Gaussian_Splatting

From Paper to Code: Understanding and Reproducing “3D Gaussian Splatting for Real-Time Radiance Field Rendering”

Chapter05_Gaussian_Image

From Paper to Code: Understanding and Reproducing “GaussianImage: 1000 FPS Image Representation and Compression by 2D Gaussian Splatting”

Chapter06_Pixel2Gaussian

From Paper to Code: Understanding and Reproducing “Pixel to Gaussian: Ultra-Fast Continuous Super-Resolution with 2D Gaussian Modeling”

Chapter07_FPM_INR

From Paper to Code: Understanding and Reproducing “Fourier ptychographic microscopy image stack reconstruction using implicit neural representations”

Chapter08_DeCAF

From Paper to Code: Understanding and Reproducing “Recovery of continuous 3D refractive index maps from discrete intensity-only measurements using neural fields”

Chapter09_Neural_SpaceTime

From Paper to Code: Understanding and Reproducing “Neural space–time model for dynamic multi-shot imaging”

Chapter10_DDPM

From Paper to Code: Understanding and Reproducing “Denoising Diffusion Probabilistic Models”

Chapter11_DPS

From Paper to Code: Understanding and Reproducing “DIFFUSION POSTERIOR SAMPLING FOR GENERAL NOISY INVERSE PROBLEMS”

Chapter12_ScoreDiffusion

From Paper to Code: Understanding and Reproducing “Score-Based Diffusion Models as Principled Priors for Inverse Imaging”

Chapter13_PlugAndPlay

From Paper to Code: Understanding and Reproducing “Plug-and-Play Image Restoration with Deep Denoiser Prior”

Chapter14_PnP-DM

Principled Probabilistic Imaging using Diffusion Models as Plug-and-Play Priors

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Index

By Xueqing Gao

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