2D techniques have recently emerged as an important boost for 3D objects content-based retrieval in many real world applications such as photography, art, archeology and geolocalization thanks to its several complementary aspects. We introduce in this paper a new framework for 3D objects content-based retrieval based on a 2D photography approach. A new alignment process that is able to find canonical views consistently through scenes/objects and a new coarse-to-fine description and matching method used for ranking are our contributions. The results are presented through an international benchmarking and showing clearly the good performance of our framework with respect to the other participants.