Master Praktikum: 3D Scanning & Spatial Learning, IN2106

Prof. Matthias NiessnerDr. Justus Thies

Studies Master Informatics
Time, Place Tuesdays, 14:00-16:00, Seminar room: MI  02.13.010 

Tuesday April 21., 2020

Kick-Off: Thursday, April 16., 2020 from 16:00-18:00 in MI  02.13.010 


3D scanning and motion capture is of paramount importance for content creation, man-machine as well as machine-environment interaction. In this course we will continue the topics covered by the 3D Scanning & Motion Capture as well as by the Introduction to Deep Learning lecture.
In the spirit of ‘learning by doing’ the students are asked to implement state-of-the-art reconstruction methods or current research topics in the field.
Specifically, we will have projects on:
- human motion capturing (e.g., Fusion4D, BodyFusion)
- real-time facial motion capturing (spare and dense approaches)
- 3D scene reconstruction (e.g., BundleFusion)
- scan refinement (e.g., ShapeFromShading)
- neural rendering of 3D content (e.g., DeepVoxel, NeuralRendering)
- scene completion (e.g., ScanComplete)
- 3D object retrieval and alignment (e.g., Scan2CAD)
- scene understanding, instance segmentation (e.g., ScanNet, 3D-SIS)

Previous Knowledge Expected:

MA0902 Analysis für Informatiker
MA0901 Lineare Algebra für Informatiker

IN2354 3D Scanning & Motion Capture (expert knowledge required!)
IN2346 Introduction to Deep Learning

This is the advanced lecture for 3D Scanning & Motion. Taking the “3D Scanning & Motion Capture” course is expected.