Work

EP-MAE: A resource-efficient masked autoencoding framework for 3D neural representation learning

Year: 2026

Type: article

Source: Neural Networks

DOI: 10.1016/j.neunet.2026.109542

Authors: Jian Zhu, Jiale Zhao, Chengxing Lin, Luan Lyu, Ruichu Cai, Xiaohua Ren, Enhua Wu

Institutions: Guangdong University of Technology, University of Electronic Science and Technology of China, Tencent (China), Chinese Academy of Sciences, University of Macau, Institute of Software

Language: English

Topic: 3D Shape Modeling and Analysis

Subfield: Computer Graphics and Computer-Aided Design

Field: Computer Science

Domain: Physical Sciences

Open Access status: closed

Funders: National Natural Science Foundation of China, Basic and Applied Basic Research Foundation of Guangdong Province

Awards: G2181580676, G4460898826, G5322437413, G636105823

OpenAlex ID: W7204013234

FWCI:

Cites: 19

Cited by:

Related to: 10