Efficient semi-supervised multiple feature fusion with out-of-sample extension for 3D model retrieval

Multi-scale object retrieval via learning on graph from multimodal data

“…Zhang et al [34] proposed to employ bipartite graph matching for 3D model comparison. Ji et al [35] proposed an efficient semi-supervised multiple feature fusion method for comparison. The bag of salient local spectrums was introduced in [36] for non-rigid and partial 3D object retrieval.…”

Learning for visual semantic understanding in big data

“…The paper by Ji et al [3] proposed to combine multiple visual features together in 3D model retrieval. An efficient Semisupervised Multiple Feature Fusion (SMFF) method was proposed for view-based 3D model retrieval.…”