Master in Computer Vision Barcelona

Deep Learning for Video

Some of the deep learning solutions for video processing included in the M6 module of the Master in Computer Vision Barcelona.

Recurrent Neural Networks RNN - Xavier Giro - UPC TelecomBCN Barcelona 2020 from Universitat Politècnica de Catalunya

Neural Architectures for Video Encoding from Universitat Politècnica de Catalunya

Deep Video Object Tracking 2020 - Xavier Giro - UPC Barcelona 2020 from Universitat Politècnica de Catalunya

Self-supervised Visual Learning 2020 - Xavier Giro-i-Nieto - UPC Barcelona from Universitat Politècnica de Catalunya

Self-supervised Audiovisual Learning 2020 - Xavier Giro-i-Nieto - UPC TelecomBCN Barcelona from Universitat Politècnica de Catalunya

Deep Learning for Video. Master in Computer Vision Barcelona. [2018]
Deep Learning for Computer Vision UPC TelecomBCN. [2016] [2017] [2018] [2019]
Deep Learning for Artificial Intelligence. UPC TelecomBCN. [2017] [2018]
Deep Learning for Speech and Language UPC TelecomBCN. [2017] [2018]
Introduction to Deep Learning. UPC TelecomBCN. [2018] [2019]
Multimodal Deep Learning. MMM 2019. [2019]
Deep Learning for Multimedia. Insight Dublin City University 2017. [2017] [2018]
Amaia Salvador and Santiago Pascual. “Hands on Keras and TensorFlow”. Persontyle 2017.
Santiago Pascual. “RNN & GANs in PyTorch”. UPC TelecomBCN 2017.

Fei-Fei Li, Andrej Karpathy, Justin Johnson, “CS231n: Convolutional Neural Networks for Visual Recognition”. Stanford University, Spring 2019.
Sanja Fidler, Machine Learning in Computer Vision. University of Toronto, Winter 2019.
Dhruv Batra, “ECE 6504: Deep learning for perception”. Virginia Tech, Fall 2015.

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