RHA-Net: An Encoder-Decoder Network with Residual Blocks and Hybrid Attention Mechanisms for Pavement Crack Segmentation. (arXiv:2207.14166v1 [cs.CV])

The acquisition and evaluation of pavement surface data play an essential
role in pavement condition evaluation. In this paper, an efficient and
effective end-to-end network for automatic pavement crack segmentation, called
RHA-Net, is proposed to improve the pavement crack segmentation accuracy. The
RHA-Net is built by integrating residual blocks (ResBlocks) and hybrid
attention blocks into the encoder-decoder architecture. The ResBlocks are used
to improve the ability of RHA-Net to extract high-level abstract features. The
hybrid attention blocks are designed to …

arxiv attention attention mechanisms cv encoder encoder-decoder hybrid network segmentation