Course Syllabus
Course Instructor and Office Hours:
Matthias Zwicker Links to an external site., office hours: by appointment, IRB5244
Time and Place:
Tuesday and Thursdays, 3:30pm-4:45pm, IRB 2207
Summary:
This course covers advanced techniques in realistic rendering and modeling for computer graphics and VR. In the first part, we will focus on realistic rendering using physically based image synthesis algorithms. Students will learn how light interacts with physical objects, and how to simulate these effects with computer algorithms to create photorealistic images. In the second part, we will discuss how to create 3D models that can be used in graphics and VR applications. We will focus on data-driven approaches, which is to leverage data captured from the physical world using cameras and 3D sensors to construct digital models. Throughout the course, we will highlight recent techniques deep learning techniques to address various problems.
Content:
To model light transport for realistic rendering, we will introduce fundamental concepts like radiometry, the bidirectional reflectance distribution function, and the rendering equation. We will discuss techniques to solve the rendering equation such as Monte Carlo path tracing, importance sampling, and photon mapping. We will also cover recent deep learning techniques that have been proposed to accelerate Monte Carlo rendering. In the second part of the course, we will cover 3D scanning and reconstruction, and texture and appearance acquisition. We will introduce 3D geometry representations such as meshes, and implicit and point-based representations, and fundamental geometry processing operations. Finally, we will discuss data-driven approaches to model 3D geometry and textures including deep learning techniques.
The course includes programming assignments related to each major topic, and a self-directed final project.
Course Schedule, Materials, and Online Communication:
The course schedule, all materials, and online communication will be managed via the course page on UMD Canvas, the electronic learning management system of UMD. Access to these resources requires login using your campus ID.
Grading:
Grading will be based on the programming assignments (40%), the final project (40%), and a final exam (20%).
Prerequisites:
An “Introduction to Computer Graphics“ (or an equivalent course) is recommended but not required. The course builds on concepts from calculus, linear algebra, and algorithms and data structures. Programming assignments rely on C++.
Academic Integrity:
We will follow the guidelines set forth by of the Department of Computer Science Links to an external site. and the Office of Student Conduct Links to an external site..
Course Summary:
Date | Details | Due |
---|---|---|
Tue Feb 4, 2020 | Assignment Assignment 1: Getting Started | due by 11:59pm |
Tue Feb 11, 2020 | Assignment Monte Carlo Integration, in-class assignment for 2/11/2020 | due by 11:59pm |
Tue Feb 18, 2020 | Assignment Assignment 2: Ray Tracing Acceleration Structures, Point Lights | due by 11:59pm |
Tue Mar 10, 2020 | Assignment Assignment 3: Monte Carlo Sampling, Area Lights, Micro-facet BRDF | due by 11:59pm |
Thu Apr 2, 2020 | Assignment March 31st, Introduction to 3D Geometry Processing | due by 11:59pm |
Sat Apr 4, 2020 | Assignment April 2nd, Point Cloud Acquisition and Alignment | due by 11:59pm |
Tue Apr 7, 2020 | Assignment Assignment 4: Monte Carlo Path Tracing | due by 11:59pm |
Thu Apr 9, 2020 | Assignment April 7th, Surface Reconstruction | due by 11:59pm |
Fri Apr 10, 2020 | Assignment Final Project: Choose your Topic | due by 11:59pm |
Sat Apr 11, 2020 | Assignment April 9th, Differential Geometry on Meshes | due by 11:59pm |
Thu Apr 16, 2020 | Assignment April 14th, Mesh smoothing | due by 11:59pm |
Sun Apr 19, 2020 | Assignment April 16, Shape deformation | due by 11:59pm |
Thu Apr 23, 2020 | Assignment April 21, Deep learning on point clouds | due by 11:59pm |
Sun Apr 26, 2020 | Assignment April 23, Upsampling point clouds via deep learning | due by 11:59pm |
Thu Apr 30, 2020 | Assignment April 28, CNNs on meshes | due by 11:59pm |
Sun May 3, 2020 | Assignment April 30, deep learning for shape synthesis | due by 11:59pm |
Thu May 7, 2020 | Assignment May 5, differentiable rendering & unsupervised 3D reconstruction | due by 11:59pm |
Sun May 10, 2020 | Assignment May 7, Neural rendering & scene representation networks | due by 11:59pm |
Tue May 19, 2020 | Assignment Final Project: Project Submission | due by 11:59pm |
Assignment May 12, Course conclusion |