EPISODE · Sep 4, 2018 · 10 MIN
Everybody Dance Now! Explained
from Siraj Raval
Everybody Dance Now is a new paper out of UC Berkeley thats able to create photorealistic video of someone dancing in the style of another, more professional dancer. Its like autotune for dance! They trained their model on a source subject (a trained dancer), then were able to transfer that dancing ability onto a target subject. In the video that was generated, the target subject takes on the source subjects dance moves as if it was their own! Incredible work, and it has huge implications for society as a whole. In this video, i'll explain the generative model they used using code and animations, as well as applications of this technology. Enjoy! Code for this video: https://github.com/llSourcell/Everybody_Dance_Now Please Subscribe! And like. And comment. That's what keeps me going. Want more education? Connect with me here: Twitter: https://twitter.com/sirajraval Facebook: https://www.facebook.com/sirajology instagram: https://www.instagram.com/sirajraval This video is apart of my Machine Learning Journey course: https://github.com/llSourcell/Machine_Learning_Journey More learning resources: https://www.reddit.com/r/MachineLearning/comments/99qkrk/ruc_berkeley_everybody_dance_now/ https://www.digitaltrends.com/cool-tech/uc-berkeley-deepfake-ai-dance/ https://www.youtube.com/watch?v=PCBTZh41Ris https://www.youtube.com/watch?v=cEBgi6QYDhQ Join us in the Wizards Slack channel: http://wizards.herokuapp.com/ Learn more about the School of AI: https://www.theschool.ai And please support me on Patreon: https://www.patreon.com/user?u=3191693 #DancingAI #SirajRaval #UCBerkeley
What this episode covers
Everybody Dance Now is a new paper out of UC Berkeley thats able to create photorealistic video of someone dancing in the style of another, more professional dancer. Its like autotune for dance! They trained their model on a source subject (a trained dancer), then were able to transfer that dancing ability onto a target subject. In the video that was generated, the target subject takes on the source subjects dance moves as if it was their own! Incredible work, and it has huge implications for society as a whole. In this video, i'll explain the generative model they used using code and animations, as well as applications of this technology. Enjoy! Code for this video: https://github.com/llSourcell/Everybody_Dance_Now Please Subscribe! And like. And comment. That's what keeps me going. Want more education? Connect with me here: Twitter: https://twitter.com/sirajraval Facebook: https://www.facebook.com/sirajology instagram: https://www.instagram.com/sirajraval This video is apart of my Machine Learning Journey course: https://github.com/llSourcell/Machine_Learning_Journey More learning resources: https://www.reddit.com/r/MachineLearning/comments/99qkrk/ruc_berkeley_everybody_dance_now/ https://www.digitaltrends.com/cool-tech/uc-berkeley-deepfake-ai-dance/ https://www.youtube.com/watch?v=PCBTZh41Ris https://www.youtube.com/watch?v=cEBgi6QYDhQ Join us in the Wizards Slack channel: http://wizards.herokuapp.com/ Learn more about the School of AI: https://www.theschool.ai And please support me on Patreon: https://www.patreon.com/user?u=3191693 #DancingAI #SirajRaval #UCBerkeley
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Everybody Dance Now! Explained
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