Deep Spherical Panoramic Representation for 3D Shape Recognition

3D shape recognition is a hot topic in recent years. This paper proposed a 3D model recognition method with multi-branch convolutional neural network（CNN） to address the problems of 3D shape representation and recognition. The inputs of the proposed method are spherical panoramas by deep spherical projection of 3D models; to improve recognition accuracy, the spherical panorama of the shape first unfolded on various orientations to produce multiple rectified images as input of recognition frame; the recognition system consists of a multi-branch CNN, which analyzes the panoramas as a whole to produce the final recognition result. The experiment results of retrieval and classification on various of 3D dataset showed that the performance of our method is better than the state-of-the-art methods, and the retrieval accuracy outperforms that of multi-view method.