Cargando…
Hierarchical Multimodal Adaptive Fusion (HMAF) Network for Prediction of RGB-D Saliency
Visual saliency prediction for RGB-D images is more challenging than that for their RGB counterparts. Additionally, very few investigations have been undertaken concerning RGB-D-saliency prediction. The proposed study presents a method based on a hierarchical multimodal adaptive fusion (HMAF) networ...
Autores principales: | Lv, Ying, Zhou, Wujie |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7700038/ https://www.ncbi.nlm.nih.gov/pubmed/33293945 http://dx.doi.org/10.1155/2020/8841681 |
Ejemplares similares
-
Deep Multimodal Fusion Autoencoder for Saliency Prediction of RGB-D Images
por: Huang, Kengda, et al.
Publicado: (2021) -
Saliency-Guided Detection of Unknown Objects in RGB-D Indoor Scenes
por: Bao, Jiatong, et al.
Publicado: (2015) -
Asymmetric Adaptive Fusion in a Two-Stream Network for RGB-D Human Detection
por: Zhang, Wenli, et al.
Publicado: (2021) -
Object recognition with hierarchical discriminant saliency networks
por: Han, Sunhyoung, et al.
Publicado: (2014) -
A New Volumetric Fusion Strategy with Adaptive Weight Field for RGB-D Reconstruction
por: Liu, Xinqi, et al.
Publicado: (2020)