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TUM Department of Informatics
Technical University of Munich

Technical University of Munich

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Informatik IX
Chair of Computer Vision & Artificial Intelligence

Boltzmannstrasse 3
85748 Garching info@vision.in.tum.de

Follow us on:
CVG Group DVL Group

News

02.10.2020

We have five papers accepted to 3DV 2020!

30.09.2020

Our effcient deep network architectures form the AI engine of the project Slow Down COVID-19 at Harvard.

24.07.2020

Our practical course "Vision-based Navigation" (WS18, SS19) by Dr. Vladyslav Usenko and Nikolaus Demmel was honored as best practical course in the academic year 2018/2019 by the department for Informatics.

07.05.2020

We are organizing a workshop on Map-based Localization for Autonomous Driving at ECCV 2020, Glasgow, UK.

13.04.2020

Daniel Cremers received an ERC Advanced Grant (3.5 Mio Euro) for pioneering frontier research from the European Research Council. This constitutes his fifth ERC grant.

More


Seminar: Current Trends in Deep Learning (IN2107, IN4515)

SS 2018, TU München

Seminar

Location: Room 02.09.023
Preliminary Meeting: 26.01.2018, 14:00 (please bring a device to access the internet)
Date: Thursday
Time: 14:00 - 16:00
Lecturer: Caner Hazirbas, Philip Haeusser
ECTS: 4
SWS: 2

The course will be held in English. Assignment to this course will be done in the matching system.

We will not favor/rank students who did not participate in the preliminary meeting.

Send your presentation via email to both advisors until 10.07.2018@23:59.

Description

Deep Learning studies computational methods that find patterns in structured data. In this seminar we will discuss current trends in deep learning based on research articles. Every student picks a recent research paper on deep learning for computer vision that she/he presents in the seminar.

Attendance is limited to 14 students (Master).
Registration: Matching system

Important Dates
Preliminary Meeting 26.01.18, 2-4pm Room 02.09.023 Please bring a device to access the internet.
First Lecture 12.04.18, 2-4pm Room 02.09.23 Intro
Second Lecture 19.04.18, 2-4pm Room 02.09.23 Paper assignment
Presentation 10.07.18, 23:59pm email Presentation submission
Preset. Day 1 11.07.18, 10:15am-6pm Room 02.09.23
Preset. Day 2 12.07.18, 10:15am-6pm Room 00.09.38
Final Report 22.07.18, 23:59pm email Report Submission


Useful Documents

Preliminary meeting presentation Lecture lecture

Paper preference form

A LaTeX-template for your seminar report latex template

Paper Assigments
StudentSupervisorPaperPresentation date
Felix MeissenPhilipMultimodal Transfer: A Hierarchical Deep Convolutional Neural Network for Fast Artistic Style Transfer12.07.18
Alexander ZillerCanerDeformable Convolutional Networks11.07.18
Marius ObertPhilipAttend in groups: a weakly-supervised deep learning framework for learning from web data12.07.18
Cem Yusuf AydogduCanerSSD: Single Shot MultiBox Detector11.07.18
Ayşe Hande KaratayPhilipLook, Listen and Learn11.07.18
Felipe PeterCanerOn-Demand Learning for Deep Image Restoration11.07.18
Yang AnPhilipDensePose: Dense Human Pose Estimation In The Wild11.07.18
Nail IbrahimliCanerUnsupervised Learning of Depth and Ego-Motion from Video12.07.18
Marvin AllesPhilipTowards 3D Human Pose Estimation in the Wild: a Weakly-supervised Approach12.07.18 - 11.07.18
Maximilian SchneiderCanerLearning to Track at 100 FPS with Deep Regression Networks11.07.18
Moritz KrügenerPhilipFast Face-swap Using Convolutional Neural Networks
Alexander GaulCanerTemporal Convolutional Networks for Action Segmentation and Detection12.07.18
Furkan Mert AlganPhilipAmbient sound provides supervision for visual learning11.07.18
Yehya AbouelnagaCanerAction-Decision Networks for Visual Tracking with Deep Reinforcement Learning12.07.18
Grading Rubric

We are going to grade you based on the following criteria:

Presentation (2/3)

  • presentation has an accessible introduction
  • presentation gets across the key idea of the paper
  • presentation style: less text on slides, more figures
  • presentation style: free but concise
  • presentation: ability to answer questions
  • active participation in discussion of other presentations

Report (1/3)

  • report is well structured
  • report reflects paper completely and correctly
  • report is written in own words, no paraphrasing
  • report contains secondary material
  • report is spell-checked and written in proper English

Rechte Seite

Informatik IX
Chair of Computer Vision & Artificial Intelligence

Boltzmannstrasse 3
85748 Garching info@vision.in.tum.de

Follow us on:
CVG Group DVL Group

News

02.10.2020

We have five papers accepted to 3DV 2020!

30.09.2020

Our effcient deep network architectures form the AI engine of the project Slow Down COVID-19 at Harvard.

24.07.2020

Our practical course "Vision-based Navigation" (WS18, SS19) by Dr. Vladyslav Usenko and Nikolaus Demmel was honored as best practical course in the academic year 2018/2019 by the department for Informatics.

07.05.2020

We are organizing a workshop on Map-based Localization for Autonomous Driving at ECCV 2020, Glasgow, UK.

13.04.2020

Daniel Cremers received an ERC Advanced Grant (3.5 Mio Euro) for pioneering frontier research from the European Research Council. This constitutes his fifth ERC grant.

More