AI Rewind continues today as we’re joined by Pavan Turaga, Associate Professor, in both the Departments of Arts, Media, and Engineering & Electrical Engineering, and the Interim Director of the School of Arts, Media, and Engineering at Arizona State University.
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Pavan, who joined us back in June to talk through his work from CVPR ‘20, Invariance, Geometry and Deep Neural Networks, is back to walk us through the trends he’s seen in Computer Vision last year. We explore the revival of physics-based thinking about scenes, differential rendering, the best papers, and where the field is going in the near future.
To follow along with the 2020 AI Rewind Series, head over to the series page!
Thanks to our Sponsor!
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Connect with Pavan
- Invariance, Geometry and Deep Neural Networks with Pavan Turaga
- NeRF Representing Scenes as Neural Radiance Fields for View Synthesis
- Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains
- Implicit Neural Representations with Periodic Activation Functions NeurIPS
- Computing the Testing Error without a Testing Set
- GANs Improve Video Conferencing with Maxine – Paper
- Neural Filters
- Check out our TWIML Presents: series page!
- Register for the TWIML Newsletter
- Check out the official TWIMLcon:AI Platform video packages here!
- Download our latest eBook, The Definitive Guide to AI Platforms!
“More On That Later” by Lee Rosevere licensed under CC By 4.0