Reading Materials

• Computer Graphics: Theory and Practice
• CreativeAI: deep learning for graphics

• Deep Learning

• Geometric Deep Learning

• Multiple View Geometry in Computer Vision

• Image Processing For Computer Graphics and Vision
• Computer Vision: Algorithms and Applications

• From Fourier Analysis to Wavelets

• Tutorial on 3D Deep Learning

• Implicit Objects in Computer Graphics
• A simple C++ geometry processing library

• Predicting Depth, Surface Normals and Semantic Labels
• 3D-R2N2: A Unified Approach for Single and Multi-view 3D Object Reconstruction
• 3D ShapeNets: A Deep Representation for Volumetric Shapes

• Occupancy Networks: Learning 3D Reconstruction in Function Space
• DeepSDF: Learning Continuous Signed Distance Functions for Shape Representation
• Implicit Neural Scene Representations with Periodic Activation Functions

• PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
• PointNet++: deep hierarchical feature learning on point sets in a metric space

• Pixel2Mesh: Generating 3D Mesh Models from Single RGB Images
• Mesh R-CNN

• Multi-view Convolutional Neural Networks for 3D Shape Recognition
• 3D Shape Segmentation with Projective Convolutional Networks

• Physically Based Rendering

• Interactive reconstruction of image sequences using a recurrent denoising autoencoder
• Kernel-predicting convolutional networks for denoising Monte Carlo renderings
• Deep Shading: Convolutional Neural Networks for Screen-Space Shading

• Soft Rasterizer: A Differentiable Renderer for Image-based 3D Reasoning
• Physics-based differentiable rendering: from theory to implementation

• Match: differentiable material graphs for procedural material capture
• MaterialGAN: reflectance capture using a generative SVBRDF model
• Learning a Neural 3D Texture Space from 2D Exemplars