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Found 4 papers, 3 papers with code
RMAFF-PSN: A Residual Multi-Scale Attention Feature Fusion Photometric Stereo Network
Predicting accurate normal maps of objects from two-dimensional images in regions of complex structure and spatial material variations is challenging using photometric stereo methods due to the influence of surface reflection properties caused by variations in object geometry and surface materials.
Exposing Image Splicing Traces in Scientific Publications via Uncertainty-guided Refinement
Compared to image duplication and synthesis, image splicing detection is more challenging due to the lack of reference images and the typically small tampered areas.
Deep Learning Methods for Calibrated Photometric Stereo and Beyond
We summarize the performance of deep learning photometric stereo models on the most widely-used benchmark data set.
Incorporating Lambertian Priors into Surface Normals Measurement
In order to address this challenge, we here propose a photometric stereo network that incorporates Lambertian priors to better measure the surface normal.
