Research on Monocular Depth Estimation Based on Diverse Branch Block
Monocular depth estimation currently has challenges such as poor accuracy and blurred object boundary depth pre-diction.In response to the above problems,this paper proposes a monocular depth estimation algorithm based on diverse-branch convolution,which uses complex convolution structure to extract richer scenes in the scene semantic information.The model uses four-branch convolution to replace the original single-branch convolution in the training phase,and the weight parameters of the di-verse-branch convolution can be transplanted to the original single-branch network during test deployment,so that no additional in-ference time is added to the network model during the testing and use phases.In the test comparison of public datasets,the depth map results predicted by the method proposed in this paper are clearer,and can effectively deal with areas such as object boundar-ies in the picture.The experimental results show that the method proposed in this paper has certain effectiveness.
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