.png){kind=icon}
返回
Depth-based adaptable image layer prediction using bidirectional depth semantic fusion
.png){kind=icon}
PRE
AI
DOI：10.1007/s00371-024-03430-2.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Image editing is a laborious process that demands considerable effort to achieve visually appealing outcomes. To address this problem, we propose a novel method depth-based adaptable image layer prediction network for multi-object semantic segmentation, localization, and estimation of the relative depths for image layer prediction. The individual objects in an image are available to be extracted and edited without impacting the background or other objects. Our approach depth semantic prediction network utilizes a fusion module to bidirectionally optimize depth estimation as well as semantic segmentation. In addition, refinement network is designed to refine coarse results into fine segmentation. Experimental results demonstrate the salient progress our method has achieved, and that it can preserve spatial hierarchical relationships and avoid category constraints as well. To the best of our knowledge, this paper introduces a novel approach to image layer prediction, which is more adaptive than the editing method focusing on foreground and background extraction.
Keyword:
Image editing
Image layer prediction
Fusion module
Depth estimation
Semantic segmentation
期刊
IF:
2.9
论文数:
4.6K
被引数:
6.5K
机构
引用论文
Effect of estrogens on bone and other systems and hormonal substitute treatment雌激素对骨骼及其他系统的影响以及激素替代治疗
PREAI
分享收藏
Preparation and microwave dielectric properties of BPO4 ceramics with ultra-low dielectric constant
PREAI
分享收藏Thermal comfort, perceived air quality, and cognitive performance when personally controlled air movement is used by tropically acclimatized persons当热带适应的人使用个人控制的空气运动时，热舒适性，感知的空气质量和认知表现.png)
Indoor Air
OAAI
Indoor AirIF0
OAAI分享收藏Depth Estimation and Semantic Segmentation from a Single RGB Image Using a Hybrid Convolutional Neural Network基于混合卷积神经网络的单幅RGB图像深度估计和语义分割SENSORSOAAI
SENSORSIF3.5
OAAI分享收藏
查看更多内容