Deep Vision

Course Information ###

 - Lecturer Dr. Frank Lenzen , Prof. Björn Ommer
 - Lecture extend (2+2 SWS)
 - Time & date: 
 - Lecture Mo 14:15-15:45
 - Exercise: Mo 16:00-17:30, 
 - Room : HCI (Speyerer Straße 6)
 - Lecture: large seminar room 2.floor room H2.22
 - Exercise : small seminar room 3rd floor 3. OG
 - Language: English

Contents ###

The lecture covers two topics:
 Topic 1: Deep Learning, in particular Deep Convolutional Neuronal Networks (CNNs). 
 As basics for Deep Neural Networks we will discuss convolutions, filters , Fourier analysis, wavelets overcomplete bases, learning, optimization, before going in to detail on neural networks.
 Topic 2: Multiview geometry and 3D scene estimation. Subtopics are camera models and camera geometry, stereo, structure from motion, optical flow, depth estimation

Misc ###

 - standard certificates ('Schein') after passing exercises and oral exam
 - certificate for attendance ('Sitzschein'): regular attendance required (absence in not more than 2 lectures )
 - Exercises partly build on MATLAB. Alternatively the students may use octave oder NumPy.

Material ###

Additional material is posted in moodle.&#13; &#13; Since currently not all students have moodle accounts, &#13; <a href=""> this </a>&#13; is an alternative link: &#13; &#13; (same password as for moodle).