Abstract : This paper presents a framework for the indexing and retrieval of artwork 3D models, allowing global and partial model classification and retrieval. The first part of the paper deals with database classification based on global shape descriptors. A search engine "RETIN-3D", using a SVM classifier coupled with an active learning strategy allows to retrieve categories of similar objects. In a second part, the classification is improved thanks to a local description of the models. A new framework for 3D surface segmentation is proposed. Shape descriptors are adapted to surface regions and kernels on descriptor bags are used to perform the database classification. Our system is designed for classifying and retrieving in ancient artwork 3D databases, and results from this application domain are presented and commented along the paper.