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Chapter and Conference Paper
Deep Shape from Polarization
This paper makes a first attempt to bring the Shape from Polarization (SfP) problem to the realm of deep learning. The previous state-of-the-art methods for SfP have been purely physics-based. We see value in ...
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Chapter and Conference Paper
MIME: Minority Inclusion for Majority Group Enhancement of AI Performance
Several papers have rightly included minority groups in artificial intelligence (AI) training data to improve test inference for minority groups and/or society-at-large. A society-at-large consists of both min...
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Chapter and Conference Paper
Not Just Streaks: Towards Ground Truth for Single Image Deraining
We propose a large-scale dataset of real-world rainy and clean image pairs and a method to remove degradations, induced by rain streaks and rain accumulation, from the image. As there exists no real-world dat...