RMAFF-PSN: A Residual Multi-Scale Attention Feature Fusion Photometric Stereo Network

arXiv:2404.07766v1 Announce Type: new
Abstract: 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. To address this issue, we propose a photometric stereo network called a RMAFF-PSN that uses residual multiscale attentional feature fusion to handle the ``difficult'' regions of the object. Unlike previous approaches that only use …

abstract arxiv attention cs.cv feature fusion geometry images influence issue maps material materials network normal object objects residual scale spatial surface type