Skip-Convolutions for Efficient Video Processing with Amir Habibian

EPISODE 496
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About this Episode

Today we kick off our CVPR coverage joined by Amir Habibian, a senior staff engineer manager at Qualcomm Technologies. In our conversation with Amir, whose research primarily focuses on video perception, we discuss a few papers they presented at the event. We explore the papers Skip-Convolutions for Efficient Video Processing, which looks at training discrete variables end to end into visual neural networks. We also discuss his work on his FrameExit paper, which proposes a conditional early exiting framework for efficient video recognition.
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Thanks to our sponsor Qualcomm AI Research

Qualcomm AI Research is dedicated to advancing AI to make its core capabilities — perception, reasoning, and action — ubiquitous across devices. Their work makes it possible for billions of users around the world to have AI-enhanced experiences on devices powered by Qualcomm Technologies. To learn more about what Qualcomm Technologies is up to on the research front, visit twimlai.com/qualcomm.

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