Deep Correlated Joint Network for 2-D Image-Based 3-D Model Retrieval

In this article, we propose a novel deep correlated joint network (DCJN) approach for 2-D image-based 3-D model retrieval. First, the proposed method can jointly learn two distinct deep neural networks, which are trained for individual modalities to learn two deep nonlinear transformations for visual feature extraction from the co-embedding feature space. Second, we propose the global loss functio...