Skip-Convolutions for Efficient Video Processing with Amir Habibian - #496
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
English - June 28, 2021 19:59 - 47 minutes - ★★★★★ - 323 ratingsTechnology News Tech News machinelearning artificialintelligence datascience samcharrington tech technology thetwimlaipocast thisweekinmachinelearning twiml twimlaipodcast Homepage Download Apple Podcasts Google Podcasts Overcast Castro Pocket Casts RSS feed
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 paper Skip-Convolutions for Efficient Video Processing, which looks at training discrete variables to 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.
The complete show notes for this episode can be found at twimlai.com/go/496.
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 paper Skip-Convolutions for Efficient Video Processing, which looks at training discrete variables to 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.
The complete show notes for this episode can be found at twimlai.com/go/496.