TIWML AI Podcast on Efficient Video Processing
Abstract
In this podcast 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.
Date
Jun 28, 2021 12:00 AM
