3 papers
cs.CV2019
Rethinking Loss Design for Large-scale 3D Shape Retrieval
Zhaoqun Li, Cheng Xu, Biao Leng
Learning discriminative shape representations is a crucial issue for large-scale 3D shape retrieval. In this paper, we propose the Collaborative Inner Product Loss (CIP Loss) to ob…
cs.CV2018
Angular Triplet-Center Loss for Multi-view 3D Shape Retrieval
Zhaoqun Li, Cheng Xu, Biao Leng
How to obtain the desirable representation of a 3D shape, which is discriminative across categories and polymerized within classes, is a significant challenge in 3D shape retrieval…
cs.CV2018
Learning Discriminative 3D Shape Representations by View Discerning Networks
Biao Leng, Cheng Zhang, Xiaocheng Zhou +2
In view-based 3D shape recognition, extracting discriminative visual representation of 3D shapes from projected images is considered the core problem. Projections with low discrimi…