Pinned Repositories
3D-Reconstruction-by-GF-4
Part of implementation of paper named Determining Both Surface Position and Orientation in Structured-Light-Based Sensing. Its abstract is Position and orientation profiles are two principal descriptions of shape in space. We describe how a structured light system, coupled with the illumination of a pseudorandom pattern and a suitable choice of feature points, can allow not only the position but also the orientation of individual surface elements to be determined independently. Unlike traditional designs which use the centroids of the illuminated pattern elements as the feature points, the proposed design uses the grid points between the pattern elements instead. The grid points have the essences that their positions in the image data are inert to the effect of perspective distortion, their individual extractions are not directly dependent on one another, and the grid points possess strong symmetry that can be exploited for their precise localization in the image data. Most importantly, the grid lines of the illuminated pattern that form the grid points can aid in determining surface normals. In this paper, we describe how each of the grid points can be labeled with a unique color code, what symmetry they possess and how the symmetry can be exploited for their precise localization at subpixel accuracy in the image data, and how 3D orientation in addition to 3D position can be determined at each of them. Both the position and orientation profiles can be determined with only a single pattern illumination and a single image capture. And the doi of the paper is 10.1109/TPAMI.2009.192.
3DCS
Three-dimensional compressive sensing algorithms
3dshearlet
3D discrete shearlet
Adaptive-Grayscale-CSI-Blue-Noise-Patterns
Simulation codes for "Adaptive Grayscale Compressive Spectral Imaging Using Optimal Blue Noise Coding Patterns"
aditof_sdk
Analog Devices 3D ToF software suite
ADMM-DIPTV
Combining Weighted Total Variation and Deep Image Prior for natural and medical image restoration via ADMM (2021)
AlphaTree-graphic-deep-neural-network
AI Roadmap:机器学习(Machine Learning)、深度学习(Deep Learning)、对抗神经网络(GAN），图神经网络（GNN），NLP，大数据相关的发展路书(roadmap), 并附海量源码（python，pytorch）带大家消化基本知识点，突破面试，完成从新手到合格工程师的跨越，其中深度学习相关论文附有tensorflow caffe官方源码，应用部分含推荐算法和知识图谱
Awesome-DL-based-CS-MRI
"Awesome-DL-based-CS-MRI" is a curated collection of resources, tools, and research papers related to deep learning-based Compressed Sensing in Magnetic Resonance Imaging (CS-MRI). It's a valuable resource for those interested in this cutting-edge field, promoting knowledge sharing and collaboration among researchers and practitioners.
In2SET
simca
Simulator for Coded Aperture Spectral Snapshot Imaging
HengJiang95's Repositories
HengJiang95/Awesome-DL-based-CS-MRI
"Awesome-DL-based-CS-MRI" is a curated collection of resources, tools, and research papers related to deep learning-based Compressed Sensing in Magnetic Resonance Imaging (CS-MRI). It's a valuable resource for those interested in this cutting-edge field, promoting knowledge sharing and collaboration among researchers and practitioners.
HengJiang95/simca
Simulator for Coded Aperture Spectral Snapshot Imaging
HengJiang95/AlphaTree-graphic-deep-neural-network
AI Roadmap:机器学习(Machine Learning)、深度学习(Deep Learning)、对抗神经网络(GAN），图神经网络（GNN），NLP，大数据相关的发展路书(roadmap), 并附海量源码（python，pytorch）带大家消化基本知识点，突破面试，完成从新手到合格工程师的跨越，其中深度学习相关论文附有tensorflow caffe官方源码，应用部分含推荐算法和知识图谱
HengJiang95/astra-toolbox
ASTRA Tomography Toolbox
HengJiang95/Awesome-Low-Level-Vision-Research-Groups
A Collection of Low Level Vision Research Groups
HengJiang95/Awesome-state-space-models
Collection of papers on state-space models
HengJiang95/ChineseResearchLaTeX
**科研常用LaTeX模板集
HengJiang95/deepinv
PyTorch library for solving imaging inverse problems using deep learning
HengJiang95/DERNN-LNLT
Code of the paper "Degradation Estimation Recurrent Neural Network with Local and Non-Local Priors for Compressive Spectral Imaging"
HengJiang95/DHM
HengJiang95/DPU
[CVPR'24] DPU: Dual Prior Unfolding for Snapshot Compressive Imaging
HengJiang95/DRNT2LRNet
HengJiang95/DRP
HengJiang95/DTDNML
Source code of our new work "Unsupervised Hyperspectral and Multispectral Image Blind Fusion Based on Deep Tucker Decomposition Network with Spatial-Spectral Manifold Learning"
HengJiang95/HEU_KMS_Activator
HengJiang95/Information_Fusion_CasFormer
Li, Chenyu, Bing Zhang, Danfeng Hong, Jun Zhou, Gemine Vivone, Shutao Li, and Jocelyn Chanussot. "CasFormer: Cascaded transformers for fusion-aware computational hyperspectral imaging." Information Fusion, 2024, 102408.
HengJiang95/MAUN
Memory-Augmented Deep Unfolding Network for Hyperspectral Image Reconstruction (IEEE/CAA Journal of Automatica Sinica 24)
HengJiang95/MEDL-Net
MEDL-Net for low-dose PET image reconstruction
HengJiang95/MLLA
Official repository of MLLA (NeurIPS 2024)
HengJiang95/MS-SSIM_L1_LOSS
Pytorch implementation of MS-SSIM L1 Loss function
HengJiang95/NLRT
HengJiang95/NTIRE2024_ESR
Solution of the NTIRE 2024 Challenge on Efficient Super-Resolution
HengJiang95/PCCGAN
Image2Points: A 3D Point-based Context Clusters GAN for High-Quality PET Image Reconstruction (ICASSP 2024)
HengJiang95/pyapetnet
a CNN for anatomy-guided deconvolution and denoising of PET images
HengJiang95/RCUMP
[TIP'24] RCUMP: Residual Completion Unrolling with Mixed Priors for Snapshot Compressive Imaging
HengJiang95/Score-Based-Generative-Models-for-PET-Image-Reconstruction
Official code for Score-Based Generative Models for PET Image Reconstruction (MELBA)
HengJiang95/SIGDUN-Net
HengJiang95/SPECAT
Official Implementation of the CVPR'24 paper: SPECAT: SPatial-spEctral Cumulative-Attention Transformer for High-Resolution Hyperspectral Image Reconstruction
HengJiang95/TIGRE
TIGRE: Tomographic Iterative GPU-based Reconstruction Toolbox
HengJiang95/x-transformers
A concise but complete full-attention transformer with a set of promising experimental features from various papers