52 min
DNN 8: Super SloMo, Computer Vision and Machine Learning Research | Varun Jampani, Google Research Deep Neural Notebooks
-
- Science
In this episode, I interview Varun Jampani, who is a Research Scientist at Google Research. You might recognise him from the renowned Super SloMo paper. His work lies at the intersection of Computer Vision and Machine Learning. His main focus is to leverage machine learning techniques for better inference in computer vision models.
Prior to joining Google, he was a research scientist at NVIDIA. He completed his PhD at the Max-Planck Institute (MPI) for Intelligent Systems. He is also a IIIT Hyderabad alum, where he did his Bachelor's and Master's.
In this episode, we talk about his journey — from his Bachelor's and Masters at IIIT Hyderabad to his PhD at MPI, about how his research has shaped over the years, about his focus on always asking good research questions and tackling fundamental problems in Computer Vision as a whole. We also talk about the SuperSloMo paper, about how it started, the key design decisions that were taken and the challenges faced in the process. If there's one thing that you are likely to take away from this conversation, it is the importance of asking good research questions and letting that drive your learning and research.
Guest:
Varun Jampani: https://varunjampani.github.io/
Links:
CVPR 2020 Novel View Synthesis Tutorial: https://www.youtube.com/watch?v=OEUHalxanuc
Episode links:
Spotify: https://tinyurl.com/y7u98d7m
Apple Podcasts: https://tinyurl.com/y8w7tkhf
Google Podcasts: https://tinyurl.com/y8aas5le
Anchor.fm: https://tinyurl.com/ycudgfse
Connect with me 🙎🏻♂️:
Twitter: twitter.com/mkulkhanna
Instagram: instagram.com/mkulkhanna/
Deep Neural Notebooks podcast 🎙:
Youtube: www.youtube.com/channel/UC66w1T4oMv66Jn1LR5CW2yg
Anchor: www.anchor.fm/deep-neural-notebooks
Spotify: www.open.spotify.com/show/2eq1jD7V5K19aZUUJnIz5z
Apple Podcasts: www.podcasts.apple.com/in/podcast/deep-neural-notebooks/id1488705711
In this episode, I interview Varun Jampani, who is a Research Scientist at Google Research. You might recognise him from the renowned Super SloMo paper. His work lies at the intersection of Computer Vision and Machine Learning. His main focus is to leverage machine learning techniques for better inference in computer vision models.
Prior to joining Google, he was a research scientist at NVIDIA. He completed his PhD at the Max-Planck Institute (MPI) for Intelligent Systems. He is also a IIIT Hyderabad alum, where he did his Bachelor's and Master's.
In this episode, we talk about his journey — from his Bachelor's and Masters at IIIT Hyderabad to his PhD at MPI, about how his research has shaped over the years, about his focus on always asking good research questions and tackling fundamental problems in Computer Vision as a whole. We also talk about the SuperSloMo paper, about how it started, the key design decisions that were taken and the challenges faced in the process. If there's one thing that you are likely to take away from this conversation, it is the importance of asking good research questions and letting that drive your learning and research.
Guest:
Varun Jampani: https://varunjampani.github.io/
Links:
CVPR 2020 Novel View Synthesis Tutorial: https://www.youtube.com/watch?v=OEUHalxanuc
Episode links:
Spotify: https://tinyurl.com/y7u98d7m
Apple Podcasts: https://tinyurl.com/y8w7tkhf
Google Podcasts: https://tinyurl.com/y8aas5le
Anchor.fm: https://tinyurl.com/ycudgfse
Connect with me 🙎🏻♂️:
Twitter: twitter.com/mkulkhanna
Instagram: instagram.com/mkulkhanna/
Deep Neural Notebooks podcast 🎙:
Youtube: www.youtube.com/channel/UC66w1T4oMv66Jn1LR5CW2yg
Anchor: www.anchor.fm/deep-neural-notebooks
Spotify: www.open.spotify.com/show/2eq1jD7V5K19aZUUJnIz5z
Apple Podcasts: www.podcasts.apple.com/in/podcast/deep-neural-notebooks/id1488705711
52 min