.png){kind=icon}
返回
Densely nested top-down flows for salient object detection
.png){kind=icon}
PRE
AI
DOI：10.1007/s11432-021-3384-y.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
With the goal of identifying pixel-wise salient object regions from each input image, salient object detection (SOD) has been receiving great attention in recent years. One kind of mainstream SOD method is formed by a bottom-up feature encoding procedure and a top-down information decoding procedure. While numerous approaches have explored the bottom-up feature extraction for this task, the design of top-down flows remains under-studied. To this end, this paper revisits the role of top-down modeling in salient object detection and designs a novel densely nested top-down flows (DNTDF)-based framework. In every stage of DNTDF, features from higher levels are read in via the progressive compression shortcut paths (PCSPs). The notable characteristics of our proposed method are as follows. (1) The propagation of high-level features which usually have relatively strong semantic information is enhanced in the decoding procedure. (2) With the help of PCSP, the gradient vanishing issues caused by non-linear operations in top-down information flows can be alleviated. (3) Thanks to the full exploration of high-level features, the decoding process of our method is relatively memory-efficient compared to those of existing methods. Integrating DNTDF with EfficientNet, we construct a highly light-weighted SOD model, with very low computational complexity. To demonstrate the effectiveness of the proposed model, comprehensive experiments are conducted on six widely-used benchmark datasets. The comparisons to the most state-of-the-art methods as well as the carefully-designed baseline models verify our insights on the top-down flow modeling for SOD.
Keyword:
salient object detection
top-down flow
densely nested framework
convolutional neural networks
期刊
IF:
7.6
论文数:
4.9K
被引数:
8.9K
机构
引用论文
LID, LEED, and Alternative Rating Systems—Integrating Low Impact Development Techniques with Green Building DesignLID，LEED和替代评级系统-将低影响开发技术与绿色建筑设计相结合
PREAI
分享收藏
Comparative study of layer by layer assembled multilayer films based on graphene oxide and reduced graphene oxide on flexible polyurethane foam: flame retardant and smoke suppression properties.png)
RSC Advances
RSC AdvancesIF0
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Indoor Air
OAAI
Indoor AirIF0
OAAI分享收藏
查看更多内容