4th Summer School

on Deep Learning for Vision


UPC ETSETB TelecomBCN (June 25 - July 3, 2019)

Deep learning technologies are at the core of the current revolution in artificial intelligence for multimedia data analysis. The convergence of large-scale annotated datasets and affordable GPU hardware has allowed the training of neural networks for data analysis tasks which were previously addressed with hand-crafted features. Architectures such as convolutional neural networks, recurrent neural networks and Q-nets for reinforcement learning have shaped a brand new scenario in signal processing. This course will cover the basic principles and applications of deep learning to computer vision problems, such as image classification, object detection or image captioning.

Open Day

Open Day

This Summer School will include a special day of oral presentations of local researchers with a high international impact.This session will be located in the Aula Master of A3 building in Campus Nord UPC (directions). These talks will be open to the general public for free, but registration will be required.

Amaia Salvador
Albert Pumarola

Syllabus (draft)

Tuesday, June 25 @ D5-010

  • 15:00 D1L1 Welcome (XG)
  • 15:25 D1L2 Neural Network Zoo (XG)
  • 15:50 D1L3 Image Classification (KM)
  • 16:15 Break
  • 16:35 D1L4 Object Detection (XG)
  • 17:00 D1L5 Face Detection & Recognition (ES)
  • 17:25 D1L6 Medical Imaging (ES)
  • 18:00 Project (KM, XG, AD, DF, AG & FR)
  • 19:00 End of the day

Wednesday, June 26 @ D5-010

  • 15:00 D2L1 Image segmentation (AP)
  • 15:25 D2L2 Object Segmentation (AP)
  • 15:50 D2L3 Video architectures I (XG)
  • 16:15 Break
  • 16:35 D2L4 Video architectures II (XG)
  • 17:00 D2L5 Object Tracking (AG)
  • 17:25 D2L6 Saliency prediction (KM)
  • 18:00 Project (KM, XG, AD, DF, AG & FR)
  • 19:00 End of the day

Thursday, June 27 @ D5-010

  • 15:00 D3L1 Similarity Learning (LL)
  • 15:25 D3L2 Bayesian Deep Learning (LL)
  • 15:50 D3L3 Noisy labels (KM)
  • 16:15 Break
  • 16:35 D3L4 Neural Network Visualization (LL)
  • 17:00 D3L5 Autoencoders (LL)
  • 17:25 D3L6 Vision & Language (AD)
  • 18:00 Project (AD, DF, LL, AG & FR)
  • 19:00 End of the day

Friday, June 28 @ Aula Master A3 (Open Day)

Monday, July 1 @ D5-010

  • 15:00 D4L1 Self-supervision (XG)
  • 15:25 D4L2 Visual generation (AP)
  • 15:50 D4L3 Vision & Audio (AD)
  • 16:15 Break
  • 16:35 D4L4 Retrieval (KM)
  • 17:00 D4L5 3D Analysis (JR)
  • 17:25 D4L6 3D Reconstruction (ER)
  • 18:00 Project (KM, XG, AD, DF, AG & FR)
  • 19:00 End of the day

Wednesday, July 3 @ D5-010

  • 15:00 Exam
  • 16:30 Student project expos
  • 18:50 Closing & homework (XG)

Check the pictures from the 2017 edition.





This Summer School requires a previous knowledge on basic deep learning techniques, which will not be covered. Please follow these indications depending on your profile:

If you have no previous experience on deep learning:

You should not sign up for this course. Build a strong basis whether by attending to our Winter School on Introduction to Deep Learning at the end of January , or signing up for the full master course of Deep Learning for Artificial Intelligence taught during Autumn.

If you can prove previous training in deep learning (eg. DLAI, IDL, or ML&DL CFIS):

  • Master students at ETSETB: Registration is available from the ETSETB academic office. There is an extraordinary registration around the end of May. You can request it from esecretaria and choose “Procedures > related to enrollment”. There you must choose “Enrollment change” or “add a subject”. Only requests made this way will be taken into account.

  • Bachelor (grau) students at ETSETB: You can register these credits as “conjunt d’activitats d’extensió universitària”. You will need to first register through this form before 10 June 2019. After the course sign up for the credits at the ETSETB academic office.

  • CFIS students: You must have completed Register directly at the CFIS academic office.

  • Master students at FIB: Contact the FIB academic office. They will collect all applications and submit them to ETSETB for approval.

  • Other students at UPC & Master in Computer Vision: You might audit the course, with no official certification. If interested, fill in this form before 10 June 2019. You may be granted a seat, if there are any available after ETSETB, CFIS & FIB students have signed up.

  • Other students at European centres in the Erasmus+ network: You can register to the course following the normal procedures of the Erasmus program. Contact the your home international office to know the details that apply to your specific case. You must have completed a Deep Learning course previously.

  • Local industry members and other students from the European Higher Education Area: You must apply for being accepted in the course and cover the 100% cost of the ECTS credits, without the support of the public funds. This corresponds to 143,08 € per ECTS credit (Summer 2016). You may have a seat, if there are any available after UPC students have signed up.If you are interested in this option, please contact send an e-mail to secretaria@etsetb.upc.edu with subject “Inscripció al seminari MET 230376 DLV”, attaching single page motivation letter stating your previous experience with deep learning, as well as a one page CV, both in PDF. Registration is limited to local industry members and students registered in an institutionfrom the European Higher Education Area.


Piazza will be used for class discussion and communication, instead of the regular UPC Atenea platform. Piazza is highly catered to getting you help fast and efficiently from classmates, TAs and instructors. Rather than emailing questions to the teaching staff, I encourage you to post your questions on Piazza. If you have any problems or feedback for the developers, email team@piazza.com.

Find us at the class page.


Previous editions

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