Cargando…
FCNet: Stereo 3D Object Detection with Feature Correlation Networks
Deep-learning techniques have significantly improved object detection performance, especially with binocular images in 3D scenarios. To supervise the depth information in stereo 3D object detection, reconstructing the 3D dense depth of LiDAR point clouds causes higher computational costs and lower i...
Autores principales: | Wu, Yingyu, Liu, Ziyan, Chen, Yunlei, Zheng, Xuhui, Zhang, Qian, Yang, Mo, Tang, Guangming |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9407267/ https://www.ncbi.nlm.nih.gov/pubmed/36010784 http://dx.doi.org/10.3390/e24081121 |
Ejemplares similares
-
Residual Learning and Multi-Path Feature Fusion-Based Channel Estimation for Millimeter-Wave Massive MIMO System
por: Zheng, Xuhui, et al.
Publicado: (2022) -
KCS-FCnet: Kernel Cross-Spectral Functional Connectivity Network for EEG-Based Motor Imagery Classification
por: García-Murillo, Daniel Guillermo, et al.
Publicado: (2023) -
Parallax attention stereo matching network based on the improved group-wise correlation stereo network
por: Yu, Xuefei, et al.
Publicado: (2022) -
LANet: Stereo matching network based on linear-attention mechanism for depth estimation optimization in 3D reconstruction of inter-forest scene
por: Liu, Lina, et al.
Publicado: (2022) -
Object-Based Change Detection Algorithm with a Spatial AI Stereo Camera
por: Göncz, Levente, et al.
Publicado: (2022)