Personalized Generative Models

Generative models are getting better these days, thanks to contributions in adversarial-based training and autoregressive models. In this talk I will describe two new generative models, one in computer vision and graphics and one for voice synthesis, with the commonality of being identity-preserving and applicable 'in-the-Wild' for the task of synthesizing a look-alike, sound-alike avatar.

Yaniv Taigman, Research Scientist at Facebook AI Research (FAIR)

I graduated from Tel-Aviv University with a Master’s in Computer Science. While pursuing my PhD research, I co-founded where I held the position of CTO. When was acquired by Facebook in 2012, I joined the office in Menlo Park to lead research and engineering projects. During this time I worked on efficient methods for face recognition (DeepFace project), and helped start the AI group. In 2016, I established a satellite FAIR team in Tel-Aviv.

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