- Houdini PDG 点云数据批量生成植被覆盖图
- Pix2pix 高度图地形生成效果
- 人脸 Mean+PCA 实验
- Mesh Deform 的一些参考
- 一些人脸重建的paper
- 网格生成优化
- Houdini PDG 点云数据批量生成高度图
- LAStools 处理点云数据
- Phase-Functioned Neural Networks for Character Control
- AIAnimation使用代码分析
- AI4Animation 工程
- AIAnimation 工程安装
- Machine Learning Techniques Lecture 15: Matrix Factorization
- Machine Learning Techniques Lecture 14: Radial Basis Function Network
- Machine Learning Techniques Lecture 13: Deep Learning
- Machine Learning Techniques Lecture 12: Neural Network
- Machine Learning Techniques Lecture 11: Gradient Boosted Decision Tree
- Machine Learning Techniques Lecture 10: Random Forest
- Machine Learning Techniques Lecture 9: Decision Tree
- Machine Learning Techniques Lecture 8: Adaptive Boosting
- Machine Learning Techniques Lecture 7: Blending and Bagging
- Machine Learning Techniques Lecture 6: Support Vector Regression
- Machine Learning Techniques Lecture 5: Kernel Logistic Regression
- Machine Learning Techniques Lecture 4: Soft-Margin Support Vector Machine
- Machine Learning Techniques Lecture 3: Kernel Support Vector Machine
- Machine Learning Techniques Lecture 2: Dual Support Vector Machine
- Machine Learning Techniques Lecture 1: Linear Support Vector Machine
- Machine Learning Foundations 16: Three Learning Principles
- Machine Learning Foundations 15: Validation
- Machine Learning Foundations 14: Regularization
- Machine Learning Foundations 13: Hazard of Overfitting
- Machine Learning Foundations 12: Nonlinear Transformation
- Machine Learning Foundations 11: Linear Models for Classification
- Machine Learning Foundations 10: Logistic Regression
- Machine Learning Foundations 9: Linear Regression
- Machine Learning Foundations 8: Noise and Error
- Machine Learning Foundations 7: The VC Dimension
- Machine Learning Foundations 6: Theory of Generalization
- Machine Learning Foundations 5: Training versus Testing
- Machine Learning Foundations 4: Feasibility of Learning
- Machine Learning Foundations 3: Types of Learning
- Machine Learning Foundations 2: Learning to Answer Yes/No
- Machine Learning Foundations 1: The Learning Problem
- Caffe 训练自有数据
- Caffe Notes
- Use Caffe windows(Microsoft)
- Book Note – Deep Learning