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Join Ads Marketplace to earn through podcast sponsorships.
Manage your ads with dynamic ad insertion capability.
Monetize with Apple Podcasts Subscriptions via Podbean.
Earn rewards and recurring income from Fan Club membership.
Get the answers and support you need.
Resources and guides to launch, grow, and monetize podcast.
Stay updated with the latest podcasting tips and trends.
Check out our newest and recently released features!
Podcast interviews, best practices, and helpful tips.
The step-by-step guide to start your own podcast.
Create the best live podcast and engage your audience.
Tips on making the decision to monetize your podcast.
The best ways to get more eyes and ears on your podcast.
Everything you need to know about podcast advertising.
The ultimate guide to recording a podcast on your phone.
Steps to set up and use group recording in the Podbean app.
Disrupting DeepFakes: Adversarial Attacks Against Conditional Image Translation Networks with Nataniel Ruiz - #375
Today we’re joined by Nataniel Ruiz, a PhD Student in the Image & Video Computing group at Boston University.
We caught up with Nataniel to discuss his paper “Disrupting DeepFakes: Adversarial Attacks Against Conditional Image Translation Networks and Facial Manipulation Systems,” which will be presented at the upcoming CVPR conference. In our conversation, we discuss the concept of this work, which essentially injects noise into an image to disrupt a generative model’s ability to manipulate said image. We also explore some of the challenging parts of implementing this work, a few potential scenarios in which this could be deployed, and the broader contributions that went into this work.
The complete show notes for this episode can be found at twimlai.com/talk/375.
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