TeachingSs18DGM

Chair for Computer Aided Medical Procedures & Augmented Reality
Lehrstuhl für Informatikanwendungen in der Medizin & Augmented Reality

Hauptseminar/Master Seminar:
Deep Generative Models SS2018

Team: Prof. Nassir Navab, Dr. Vasileios Belagiannis, Dr. Federico Tombari, Iro Laina, Magda Paschali, Leslie Casas, Oliver Scheel

Type: Advanced Seminar Course Module IN0014
Type: Master Seminar Module IN2107
Type: Seminar Module IN4826
SWS: 2+0
ECTS: 5 Credits
Location: MI 03.13.010
Time: 16:00 - 18:00
Course Language: English

Announcements

  • 03.02.2018 - Motivation letters are welcomed.
  • 21.01.2018 - Preliminary meeting 25.01.2018 at 11:00 - 12:00 at MI 03.13.010.
  • 14.01.2018 - The seminar Deep Generative Models will be offered for the Summer Semester 2018. The web-site will be updated soon.

Introduction

  • The recent advances of generative models in Deep Learning will be studied in the Seminar Course. Variational Autoencoders (VAEs), Generative Adversarial Networks (GANs), adversarial learning and learning with adversaries compose the main topics of the seminar. A set of papers will cover the aforementioned topics. One or two lectures will be also offered to support the seminar.

Registration

  • Preliminary Meeting: 25.01.2018 at 11:00 - 12:00 at MI 03.13.010.
  • The registration is though the TUM Matching Platform.

Requirements

In this Seminar (formerly Hauptseminar), each student is asked to select one paper from a list. In order to successfully complete the seminar, participants have to fulfill these requirements:

  • Presentation: The selected paper is presented to the other participants (20 minutes presentation 10 minutes questions). Use the CAMP templates for PowerPoint camp-tum-jhu-slides.zip, or Latex: CAMP-latex-template.
  • Written Report: A document of maximum 8 pages is written and submitted one week after the presentation. Please download and use the llncs2e.zip Latex template.
  • Attendance: Participants have to participate actively in all seminar sessions.

The students are required to attend each seminar presentation which will be held during this course. Each presentation is followed by a discussion and everyone is encouraged to actively participate. Part of the discussions outcome will be included in the report too. The report must include all references used and must be written completely in your own words. Copy and paste will not be tolerated. Both report and presentation have to be done in English.

List of Publications

Nr Authors Title Conference Link Tutor Student
01 Arjovsky, Martin and Bottou Leon Towards principled methods for training generative adversarial networks ICLR 2017 https://arxiv.org/pdf/1701.04862.pdf Vasilis Fabian H.
02 Ilya Tolstikhin, Olivier Bousquet, Sylvain Gelly, Bernhard Schoelkopf Wasserstein Auto-Encoders ICLR 2018 https://arxiv.org/abs/1711.01558 Kristians Nathanael B.
03 Justin Johnson, Alexandre Alahi, Li Fei-Fei Perceptual Losses for Real-Time Style Transfer and Super-Resolution ECCV 2016 https://arxiv.org/abs/1603.08155 Oliver Sangram G.
04 Ashish Bora, Eric Price, Alexandros G. Dimakis AmbientGAN?: Generative models from lossy measurements ICLR 2018 https://openreview.net/forum?id=Hy7fDog0b Helisa Deepita P.
05 Achlioptas, Panos and Diamanti, Olga and Mitliagkas, Ioannis and Guibas, Leonidas Learning Representations and Generative Models for 3D Point Clouds arxiv 2017 https://arxiv.org/abs/1707.02392 Federico Thi Kim T. T.
06 Anh Nguyen, Jeff Clune, Yoshua Bengio, Alexey Dosovitskiy, Jason Yosinski Plug & Play Generative Networks: Conditional Iterative Generation of Images in Latent Space CVPR 2017 https://arxiv.org/abs/1612.00005 Kristians Pooja K.
07 Jiajun Wu, Chengkai Zhang, Tianfan Xue, William T. Freeman, Joshua B. Tenenbaum Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial Modeling NIPS 2016 https://arxiv.org/abs/1610.07584 Federico Henrique R.
08 Yunchen Pu, Weiyao Wang, Ricardo Henao, Liqun Chen, Zhe Gan, Chunyuan Li, Lawrence Carin Adversarial Symmetric Variational Autoencoder NIPS 2017 https://arxiv.org/abs/1711.04915 Leslie Karl S.
09 Qi Wu, Peng Wang, Chunhua Shen, Ian Reid, Anton van den Hengel Are You Talking to Me? Reasoned Visual Dialog Generation through Adversarial Learning CVPR 2018 https://arxiv.org/abs/1711.07613 Iro Farrukh M.
10 William Fedus, Mihaela Rosca, Balaji Lakshminarayanan, Andrew M. Dai, Shakir Mohamed, Ian Goodfellow Many Paths to Equilibrium: GANs Do Not Need to Decrease a Divergence At Every Step ICLR 2018 https://openreview.net/forum?id=ByQpn1ZA- Oliver Juliane A.
11 Gamaleldin F. Elsayed, Shreya Shankar, Brian Cheung, Nicolas Papernot, Alex Kurakin, Ian Goodfellow, Jascha Sohl-Dickstein Adversarial Examples that Fool both Human and Computer Vision Arxiv 2018 https://arxiv.org/abs/1802.08195 Magda Jonas H.
12 Nir Baram, Oron Anschel, Itai Caspi, Shie Mannor End-to-End Differentiable Adversarial Imitation Learning ICML 2017 http://proceedings.mlr.press/v70/baram17a/baram17a.pdf Vasilis Harris J.
13 Ashish Shrivastava, Tomas Pfister, Oncel Tuzel, Josh Susskind, Wenda Wang, Russ Webb Learning from Simulated and Unsupervised Images through Adversarial Training CVPR 2017 https://arxiv.org/abs/1612.07828 Leslie Shyam A.
14 Ishaan Gulrajani, Faruk Ahmed, Martin Arjovsky, Vincent Dumoulin, Aaron Courville Improved Training of Wasserstein GANs. NIPS 2017 https://arxiv.org/pdf/1704.00028.pdf Magda Yelysei B.

Schedule

The schedule for the paper presentations will be announced here during the semester. Each student is required to attend all presentations.

Date Time Title Speaker Material
18.04.2018 16:00 - 18:00 Lecture Vasileios Belagiannis Slides, Code
25.04.2018 16:00 - 18:00 3 Presentations (tbd) Fabian H., Nathanael B., Sangram G.  
02.05.2018 16:00 - 18:00 3 Presentations (tbd) Deepita P., Thi Kim T. T., Pooja K.
 
09.05.2018 16:00 - 18:00 3 Presentations (tbd) Henrique R., Karl S., Farrukh M.  
23.05.2018 16:00 - 18:00 3 Presentations (tbd) Juliane A., Jonas H.  
06.06.2018 16:00 - 18:00 2 Presentations (tbd) Shyam A., Yelysei B., Harris J.
 

TeachingForm
Title: Deep Generative Models
Professor: Prof. Nassir Navab, Dr. Vasileios Belagiannis, Dr. Federico Tombari
Tutors: Iro Laina, Magda Paschali
Type: Hauptseminar
Information: Hauptseminar, SWS: 2, ECTS: 5
Term: 2018SoSe
Abstract:  


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