UNC COMP 790 177 Neural Rendering
COMP 590/790: Neural Rendering
Goal/Student Learning Outcomes
590: (a) Understand an overview of 2D & 3D Neural Rendering (b) Learn how to code and synthesize 2D and 3D content in Pytorch
790: (a) Understand details of different recent techniques in Neural Rendering (b) Learn how to code and synthesize 2D and 3D content in Pytorch (c) Formulate novel project ideas and explore new solutions in the field of image/video synthesis and 3D reconstruction.
Grading: for 590
- 2 Paper Summary: 20 points
- Assignment 1: Train neural network for image classification: 10 points
- Assignment 2: Train DCGAN: 20 points
- Assignment 3: Test StyleGAN Inversion and editing: 20 points
- Assignment 4: Generate new images from text and sketch using Stability Diffusion: 10 points
- Assignment 5: Train Tiny-NeRF (Neural Radiance Field): 20 points
Students who have registered for 590 but want to engage in research projects can opt for 790 grading system. You have to declare your intention by Aug 25 by sending me an email.
Grading: for 790
- 2 Paper Presentation/ Review: 20 points (Some students will do 2 presentations, some will do 1 presentation + 1 review)
- Assignment 1: Generate new images from text and sketch using Stability Diffusion: 10 points
- Assignment 2: Train NeRF on pre-captured and self-captured imagery: 20 points
- Course Project: 50 points
COMP 590 Assignment 1: CIFAR10 - Google Docs
COMP 590 Assignment 2: DCGAN - Google Docs
COMP 590 Assignment 3: StyleGAN - Google Docs
COMP 590/790 Diffusion Model Assignment - Google Docs