当前位置: X-MOL 学术Vis. Comput. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Instance-level 3D shape retrieval from a single image by hybrid-representation-assisted joint embedding
The Visual Computer ( IF 3.5 ) Pub Date : 2020-07-31 , DOI: 10.1007/s00371-020-01935-0
Qian-Fang Zou , Ligang Liu , Yang Liu

We present a novel and effective joint embedding approach for retrieving the most similar 3D shape for a single image query. Our approach builds upon hybrid 3D representations—the octree-based representation and the multi-view image representation, which characterize shape geometry in different ways. We first pre-train a 3D feature space via jointly embedding 3D shapes with hybrid representations and then introduce a transform layer and an image encoder to map both shape codes and real images into a common space via a second joint embedding. Our pre-training benefits from the hybrid representation of 3D shapes and builds a more discriminative 3D shape space than using any one of 3D representations only. The transform layer helps to mind the gap between the 3D shape space and the real image space. We validate the efficacy of our method on the instance-level single-image 3D retrieval task and achieve significant improvements over existing methods.

中文翻译:

通过混合表示辅助联合嵌入从单个图像中检索实例级 3D 形状

我们提出了一种新颖有效的联合嵌入方法,用于为单个图像查询检索最相似的 3D 形状。我们的方法建立在混合 3D 表示的基础上——基于八叉树的表示和多视图图像表示,它们以不同的方式表征形状几何。我们首先通过联合嵌入具有混合表示的 3D 形状来预训练 3D 特征空间,然后引入一个变换层和一个图像编码器,通过第二个联合嵌入将形状代码和真实图像映射到公共空间。我们的预训练受益于 3D 形状的混合表示,并构建了比仅使用任何一种 3D 表示更具辨别力的 3D 形状空间。变换层有助于注意 3D 形状空间和真实图像空间之间的差距。
更新日期:2020-07-31
down
wechat
bug