GARNet: Global-aware multi-view 3D reconstruction network and the cost-performance tradeoff

Zhenwei Zhu, Liying Yang, Xuxin Lin, Lin Yang, Yanyan Liang

Abstract: Highlights•For multi-view input, we propose the global-aware fusion to adapt the global state when fusing features from different views.•Our algorithm includes a powerful but relatively lightweight network, novel loss function, and specified training strategy.•The reconstructor exceeds existing SOTA methods while the amount of parameters is far less than the same type of algorithm.•An extra view-reduction method based on maximizing diversity for our model can be used to tradeoff cost and performance.

External IDs:doi:10.1016/j.patcog.2023.109674