Skip-Convolutions for Efficient Video Processing with Amir Habibian

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.