Multi-View Three-Dimensional Model Retrieval Method Based on Non-Local Graph Convolutional Network

The present invention relates to the field of computer vision and deep learning. In order to address the drawbacks in the existing view-based deep learning methods that they cannot capture comprehensive spatial information of a 3D model, the present invention provides a multi-view 5 three-dimensional model retrieval method based on non-local graph convolutional network, which explores and fuses high response features of multiple views and thus obtains a single, compact, highly discriminative model descriptor. Its excellent performance has been verified in 3D model retrieval. The present invention includes the following steps: (1) acquiring multi perspective images of a model, (2) preprocessing the multi-perspective images, (3) designing a 0 non-local graph convolutional network, (4) training the non-local graph convolutional network, (5) extracting model depth features, (6) retrieval and matching of three-dimensional model. uQ u Q o Q - o - ) u A -,o A o u Q ] T -- -E >