Overivew


Organizers

Ming-Yu Liu, Senior Research Scientist at Nvidia Research
[Google Scholar]

Min Sun, Assistant Professor in Electrical Engineering
at National Tsing Hua University
[Google Scholar]


Tutorial Info

  • Date: Nov. 24

    Time: 02:00pm-05:00pm.

    Location: room 101B


Schedule

  • 02:00pm-02:50pm

    Introduction to deep learning in computer vision
    We will introduce the standard supervised deep learning model such as CNN and RNN. The introduction will include: a brief history of the development of both models, their model architectures and intuition, training methods and tips for learning a good model.

  • 02:50pm-03:10pm

    Coffee Break

  • 03:10pm-04:00pm

    Deep learning for vision and language
    We will introduce a number of recent works related to image captioning, image question answering, video captioning, and video question answering. Our introduction includes new deep learning models to combine vision and language, popular dataset, and future challenges.

  • 04:10-5:00pm

    Deep learning for image generation
    We will introduce a number of recent deep learning works on image generation. Various practical algorithm design issues will be discussed. Particularly. we will highlight the generative adversarial network problem.


Reference

  • Ian Goodfellow and Yoshua Bengio and Aaron Courville, Deep Learning, MIT Press 2016

  • Ian J. Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, Yoshua Bengio, Generative Adversarial Networks, NIPS 2014

  • Alec Radford, Luke Metz, Soumith Chintala, Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks, ICLR 2016

  • Tim Salimans, Ian Goodfellow, Wojciech Zaremba, Vicki Cheung, Alec Radford, Xi Chen, Improved Techniques for Training GANs, NIPS 2016

  • Ming-Yu Liu and Oncel Tuzel, Coupled Generative Adversarial Networks, NIPS 2016

  • Kuo-Hao Zeng, Tseng-Hung Chen, Juan Carlos Niebles, and Min Sun, Video Title Generation, ECCV 2016

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