We continue our CVPR coverage with today’s guest, Pavan Turaga, Associate Professor at Arizona State University, with dual appointments as the Director of the Geometric Media Lab, and Interim Director of the School of Arts, Media, and Engineering.
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Pavan gave a keynote presentation at the Differential Geometry in CV and ML Workshop, speaking on Revisiting Invariants with Geometry and Deep Learning. In our conversation, we go in-depth on Pavan’s research integrating physics-based principles into computer vision. We also discuss the context of the term “invariant,” and the role of architectural, loss function, and data constraints on models. Pavan also contextualizes this work in relation to Hinton’s similar Capsule Network research.
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Connect with Pavan!
Resources
- Check out Pavan’s CVPR Workshop Presentation: Revisiting Invariants with Geometry and Deep Learning
- Differential Geometry in Computer Vision and Machine Learning Workshop
- Paper: Measuring Invariences in Deep Learning
- Paper: Classification of Gait Patterns
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“More On That Later” by Lee Rosevere licensed under CC By 4.0
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