通过多视图三维重建获得三维模型，用于有限元分析/工业设计指导
Unpack Game File (Snowbreak)
Anime Image 3D Reconstruction
Loss Functions
Loss Functions and Metrics in Deep Learning 这篇Review中提到的loss函数比较全面
Loss Functions vs. Performance Metrics
损失函数在训练过程中用于优化模型参数。它衡量的是模型预测输出与预期输出之间的差值，而训练的目标就是尽量减小这一差值。(可微)
性能指标用于评估训练后的模型。它衡量的是模型对新数据的泛化程度以及预测的准确性。性能指标还可以对不同的模型或配置进行比较，以确定性能最佳的模型或配置。(不需要可微)
Finite Element Learning Note
Basic of Finite Element Analysis
Nastran by python
Python—> Nastran
使用PyNastran库对 Patran&Nastran有限元分析软件进行二次开发，可以自动对目标模型进行有限元分析
Concrete spalling damage detection and seismic performance evaluation for RC shear walls via 3D reconstruction technique and numerical model updating
| Title | Concrete spalling damage detection and seismic performance evaluation for RC shear walls via 3D reconstruction technique and numerical model updating |
|---|---|
| Author | Weihang Gao; Caiyan Zhang; Xilin Lu; Wensheng Lu |
| Conf/Jour | Automation in Construction |
| Year | 2023 |
| Project | Concrete spalling damage detection and seismic performance evaluation for RC shear walls via 3D reconstruction technique and numerical model updating - ScienceDirect |
| Paper |
3D reconstruction+Numerical model updating
Learn-Matlab
Matlab
Gaustudio
| Title | GauStudio: A Modular Framework for 3D Gaussian Splatting and Beyond |
|---|---|
| Author | Chongjie Ye1,2∗, Yinyu Nie3∗, Jiahao Chang1, 2∗, Yuantao Chen2, Yihao Zhi1,2, Xiaoguang Han2,1† |
| Conf/Jour | |
| Year | 2024 |
| Project | GAP-LAB-CUHK-SZ/gaustudio: A Modular Framework for 3D Gaussian Splatting and Beyond |
| Paper | GauStudio-v1.pdf - Google 云端硬盘 |
2DGS
| Title | 2D Gaussian Splatting for Geometrically Accurate Radiance Fields |
|---|---|
| Author | Binbin Huang, Zehao Yu, Anpei Chen, Andreas Geiger, Shenghua Gao |
| Conf/Jour | |
| Year | 2024 |
| Project | 2D Gaussian Splatting |
| Paper | [2403.17888] 2D Gaussian Splatting for Geometrically Accurate Radiance Fields |
Math
概率/微积分/矩阵/拓扑/泛函…
MATH $e^{i\pi}+1=0$
Linux
Single-view Reconstruction Review
The review about 3D Reconstruction from a single image.
LoD-NeuS
| Title | LoD-NeuS: Anti-Aliased Neural Implicit Surfaces with Encoding Level of Detail |
|---|---|
| Author | Zhuang, Yiyu and Zhang, Qi and Feng, Ying and Zhu, Hao and Yao, Yao and Li, Xiaoyu and Cao, Yan-Pei and Shan, Ying and Cao, Xun |
| Conf/Jour | arXiv |
| Year | 2023 |
| Project | NeIF (nju-3dv.github.io) |
| Paper | Anti-Aliased Neural Implicit Surfaces with Encoding Level of Detail (readpaper.com) |
NeuSurf
| Title | NeuSurf: On-Surface Priors for Neural Surface Reconstruction from Sparse Input Views |
|---|---|
| Author | Han Huang1,2, Yulun Wu1,2, Junsheng Zhou1,2, Ge Gao1,2*, Ming Gu1,2, Yu-Shen Liu2 |
| Conf/Jour | arXiv |
| Year | 2023 |
| Project | |
| Paper | NeuSurf: On-Surface Priors for Neural Surface Reconstruction from Sparse Input Views (readpaper.com) |
Stereo Matching Review
双目立体匹配
SuGaR
| Title | SuGaR |
|---|---|
| Author | Gu{\'e}don, Antoine and Lepetit, Vincent |
| Conf/Jour | CVPR |
| Year | 2024 |
| Project | Anttwo/SuGaR: Official implementation of SuGaR: Surface-Aligned Gaussian Splatting for Efficient 3D Mesh Reconstruction and High-Quality Mesh Rendering (github.com) |
| Paper | SuGaR: Surface-Aligned Gaussian Splatting for Efficient 3D Mesh Reconstruction and High-Quality Mesh Rendering |