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Deep learning-based photometric stereo

This work is the first photometric stereo method based on deep learning. Our method uses a deep neural network to model reflectances in the real world. As a result, our method achieved the best results compared to conventional methods in DiLiGenT Benchmark comparison. [Project Page]


  • Hiroaki Santo, Masaki Samejima, Yusuke Sugano, Boxin Shi, and Yasuyuki Matsushita: Deep photometric stereo network, International Workshop on Physics Based Vision meets Deep Learning (PBDL) in Conjunction with IEEE International Conference on Computer Vision (ICCV), Venice, Italy (Oct. 2017).
Matsushita Lab. (HOME)