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Neural Architecture Search for Efficient Uncalibrated Deep Photometric Stereo
(2022)2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)We present an automated machine learning approach for uncalibrated photometric stereo (PS). Our work aims at discovering lightweight and computationally efficient PS neural networks with excellent surface normal accuracy. Unlike previous uncalibrated deep PS networks, which are handcrafted and carefully tuned, we leverage differentiable neural architecture search (NAS) strategy to find uncalibrated PS architecture automatically. We begin ...Conference Paper