This seminar covers advanced topics in visual computing, including both seminal research papers as well as the latest research results. The main topic areas are image and video processing, capture, rendering, visualization, simulation, fabrication as well as machine learning in graphics.
Every participant has to present one of the papers in the list below. Additionally, you are required to read the paper that is presented in class beforehand and participate in a discussion during the seminar. An assistant will provide support when preparing the slides and in case technical questions arise.
The goal is to get an in-depth understanding of actual problems and research topics in the field of visual computing as well as improve presentations and critical analysis skills.
The "Visual Computing", "Introduction to Computer Graphics" and "Computer Vision I" courses are recommended, but not mandatory.
Presence is mandatory to pass the seminar. If a student cannot attend a seminar session, the reason (e.g. medical certificate) has to be given before the session and must be accepted by one of the organizers. More than three missed seminar sessions will cause the student to fail this class. The dates for the presentations can not be moved except there is someone willing to switch.
The presentation of the selected paper contributes 75% to the final grade. Additionally, the students are required to submit a short abstract of each paper before the class as well as to participate in the group discussions after the presentations. Both will be documented by the organizers and contributes 25% to the final grade.
| Number | 252-5704-00L |
| Lecturers | M. Gross, B. Solenthaler, O. Sorkine-Hornung |
| Location | CHN F 42, Tuesdays 12:15-14:00 |
| Date | Paper |
| 17-Feb | Introduction [ Slides | Paper List ] |
| 24-Feb | How To Present [ Slides ] |
| 03-Mar | Dual Contouring of Hermite Data |
| 03-Mar | Flexible Isosurface Extraction for Gradient-Based Mesh Optimization |
| 10-Mar | Strand-accurate Multi-view Hair Capture |
| 10-Mar | Neural Strands: Learning Hair Geometry and Appearance from Multi-View Images |
| 17-Mar | HairNet: Single-View Hair Reconstruction using Convolutional Neural Networks |
| 17-Mar | The Impulse Particle in cell Method |
| 24-Mar | Unified Particle Physics for Real-Time Applications |
| 24-Mar | Large Steps in Cloth Simulation |
| 31-Mar | A Stream Function Solver for Liquid Simulations |
| 31-Mar | Deep Fluids: A Generative Network for Parameterized Fluid Simulations |
| 07-Apr | Easter- No Class |
| 14-Apr | FLAME: Learning a model of facial shape and expression from 4D scans ( + SMPL) |
| 14-Apr | Continuous Remeshing For Inverse Rendering |
| 21-Apr | Shape Transformers: Topology-Independent 3D Shape Models Using Transformers |
| 21-Apr | Representing Scenes as Neural Radiance Fields for View Synthesis |
| 28-Apr | Instant Neural Graphics Primitives with a Multiresolution Hash Encoding |
| 28-Apr | 3D Gaussian Splatting for Real-Time Radiance Field Rendering |
| 05-May | Mip-Splatting: Alias-free 3D Gaussian Splatting |
| 05-May | ScaffoldAvatar: High-fidelity Gaussian avatars with patch expressions |
| 12-May | DINO v2/v3: Learning robust visual features without supervision |
| 19-May | No class |
| 26-May | No class |