Learning for 3D Homeworks

Homeworks in CMU 16-825: Learning for 3D Vision.

Assignment1: Rendering Basics with PyTorch3D

Practicing with Cameras

Rendering Your First Mesh

Practicing with Cameras

360-degree Renders

Re-creating the Dolly Zoom

Practicing with Meshes

Constructing a Tetrahedron

Constructing a Cube

Re-texturing a Mesh

Rendering Generic 3D Representations

Rendering Point Clouds from RGB-D Images

Parametric Functions

Implicit Surfaces

Sampling Points on Meshes

Assignment2: Single View to 3D

Exploring Loss Functions

Reconstructing 3D from Single View

Assignment3: Volume Rendering, Neural Radiance Fields, Neural Surfaces

Neural Volume Rendering

Neural Surface Rendering

Assignment4: 3D Gaussian Splatting and Diffusion Guided Optimization

3D Gaussian Splatting

Diffusion-guided Optimization

Assignment5: Point Cloud Processing

PointNet for Segmentation

PointNet++ for Segmentation