Computer Graphics Laboratory

Course Topics

This seminar covers advanced topics in visual computing, including both seminal research papers as well as the latest research results. Topics include data-driven modeling and animation, image based rendering, real-time vision & graphics, physical simulation and generative models, visual perception, computational photography, video synthesis, and others.

Course Setup

Every participant has to present one of the papers presented in the first session. 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.

Important remarks

• Participants who registered to the course and selected a paper have to present their paper during the semester. In addition each participant has to attend all presentations (3 misses allowed).
  In case these requirements are not met, the course is not passed (fail score).
• Participants are only allowed to unregister the course before they have chosen a paper to present.
• Participants who are not registered to the course (e.g. because there are no more free slots), are welcome to attend the first session to fill empty slots.
• It is not allowed to use the original slides from the author (please prepare the slides to fit an aspect ratio of 16:10).

Learning Objectives

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.

Prerequisites

The "Visual Computing", "Introduction to Computer Graphics" and "Computer Vision I" courses are recommended, but not mandatory.

Administration

Schedule

Date	Name	Topic	Supervisor
Sept 19		Introduction and paper assignments
Sept 26		Example Talk
Oct 03	Michael A. Flückiger	PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation	Liu Peidong
Oct 03	Christian Knieling	DeepSDF: Learning Continuous Signed Distance Functions for Shape Representation	Shihao Wu
Oct 10	Oliver Blaser	Distortion-Free Wide-Angle Portraits on Camera Phones	Daniel Thul
Oct 10	Qais El Okaili	Transport-Based Neural Style Transfer for Smoke Simulations	Byungsoo Kim
Oct 17	Melih Arda Duzceker	Direct Sparse Odometry	Zuo Xingxing
Oct 17	Zsombor Kalotay	3D human pose estimation in video with temporal convolutions and semi-supervised training	Jakob Buhmann
Oct 24	Alberto Pennino	Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks	Songyou Peng
Oct 24	Daoye Wang	Fourier Opacity Optimization for Scalable Exploration	Irene Baeza Rojo
Oct 31	Lixin Xue	What Do Single-view 3D Reconstruction Networks Learn?	Viktor Larsson
Oct 31	Jonas Hein	Hand Keypoint Detection in Single Images using Multiview Bootstrapping	Taein Kwon
Nov 7	Jan Leutwyles	A Stream Function Solver for Liquid Simulations	Vinicius C. Azevedo
Nov 7	Kaifeng Zhao	SceneCode: Monocular Dense Semantic Reconstruction using Learned Encoded Scene Representations	Silvan Weder
Nov 14	Jin Schengze	MeshCNN: A Network with an Edge	Radek Danecek
Nov 14	Yufeng Zheng	Learning Efficient Point Cloud Generation for Dense 3D Object Reconstruction	Yang Zhang
Nov 21	Aaron Keller	Interactive Hand Pose Estimation using a Strech-Sensing Soft Glove	Shihao Wu
Nov 21	Guohao Zhang	MegaDepth: Learning Single-View Depth Prediction From Internet Photos	Mihai Dusmanu
Nov 28	Matteo Signer	Authoring Landscapes by Combining Ecosystem and Terrain Erosion Simulation	Guillaume Cordonnier
Nov 28	Nihat Isik	Deferred Neural Rendering: Image Synthesis using Neural Textures	Aziz Djelouah
Dez 5	Jordan Burklund	Semantic Visual Localization	Marcel Geppert
Dez 5	Nino Schesser	A Style-Based Generator Architecture for Generative Adversarial Networks	Martin Guay
Dez 12	Alessia Paccagnella	An Advection-Reflection Solver for Detail-Preserving Fluid Simulation	Vinicius C. Azevedo
Dez 12	Florian Behrens	Discriminative Correlation Filter with Channel and Spatial Reliability	Denys Rozumnyi