Cargando…
Predicting Depth from Single RGB Images with Pyramidal Three-Streamed Networks
Predicting depth from a monocular image is an ill-posed and inherently ambiguous issue in computer vision. In this paper, we propose a pyramidal third-streamed network (PTSN) that recovers the depth information using a single given RGB image. PTSN uses pyramidal structure images, which can extract m...
Autores principales: | Chen, Songnan, Tang, Mengxia, Kan, Jiangming |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6386885/ https://www.ncbi.nlm.nih.gov/pubmed/30736347 http://dx.doi.org/10.3390/s19030667 |
Ejemplares similares
-
TMSCNet: A three-stage multi-branch self-correcting trait estimation network for RGB and depth images of lettuce
por: Zhang, Qinjian, et al.
Publicado: (2022) -
Depth Estimation and Semantic Segmentation from a Single RGB Image Using a Hybrid Convolutional Neural Network
por: Lin, Xiao, et al.
Publicado: (2019) -
Asymmetric Adaptive Fusion in a Two-Stream Network for RGB-D Human Detection
por: Zhang, Wenli, et al.
Publicado: (2021) -
Absolute and Relative Depth-Induced Network for RGB-D Salient Object Detection
por: Kong, Yuqiu, et al.
Publicado: (2023) -
A Hybrid Network for Large-Scale Action Recognition from RGB and Depth Modalities
por: Wang, Huogen, et al.
Publicado: (2020)