Deep point-to-subspace metric learning for sketch-based 3D shape retrieval.

•A representative-view selection (RVS) module is designed to identify the most representative views of a 3D shape for reducing the redundancy.•A deep point-to-subspace metric learning (DPSML) module is proposed to calculate the query-adaptive similarity for sketch-based 3D shape retrieval.•The representation learning problem is formulated as a classification problem with a specially designed classifier and training loss.•State-of-the-art performance on SHREC 2013, 2014 and 2016 benchmarks are achieved.