  The quick and accurate retrieval of an object height from a single fringe
pattern in Fringe Projection Profilometry has been a topic of ongoing research.
While a single shot fringe to depth CNN based method can restore height map
directly from a single pattern, its accuracy is currently inferior to the
traditional phase shifting technique. To improve this method's accuracy, we
propose using a U shaped High resolution Network (UHRNet). The network uses
UNet encoding and decoding structure as backbone, with Multi-Level convolution
Block and High resolution Fusion Block applied to extract local features and
global features. We also designed a compound loss function by combining
Structural Similarity Index Measure Loss (SSIMLoss) function and chunked L2
loss function to improve 3D reconstruction details.We conducted several
experiments to demonstrate the validity and robustness of our proposed method.
A few experiments have been conducted to demonstrate the validity and
robustness of the proposed method, The average RMSE of 3D reconstruction by our
method is only 0.443(mm). which is 41.13% of the UNet method and 33.31% of Wang
et al hNet method. Our experimental results show that our proposed method can
increase the accuracy of 3D reconstruction from a single fringe pattern.
