.png){kind=icon}
返回
Positive-Incentive Pseudo Label Optimization for Salient Object Detection
.png){kind=icon}
OA
AI
DOI：10.1109/ACCESS.2024.3476077.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
We present a salient object detection method in this paper. It uses a lightweight network based on multi-scale information aggregation (MIA) module and bidirectional cross-stage feature fusion (BCF2) module to speed up the reasoning process. Besides, it designs a stepwise coupling optimization strategy based on positive-incentive pseudo label to alleviate the miss detection rate for small objects and the false detection rate for big objects. It is worth noting that the positive-incentive pseudo label generation mechanism can increase the ratio of salient pixels in small objects to alleviate the severe category imbalance problem, while the stepwise coupling optimization strategy can avoid the misguidance of pseudo label to big objects. In addition, the experimental results demonstrate that our method is fairly efficient, its frame rate in reasoning phase reaches 275.6 FPS on NVIDIA RTX3080 GPU when the input resolution is set to 336 x 336
Keyword:
Salient object detection
high-efficiency
positive-incentive pseudo label
lightweight network
Salient object detection
high-efficiency
positive-incentive pseudo label
lightweight network
期刊
IF:
3.6
论文数:
9.8W
被引数:
29.4W
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
.png){kind=icon}
PREAI
分享收藏CATNet: A Cascaded and Aggregated Transformer Network for RGB-D Salient Object DetectionCATNet: 用于rgb-d显着目标检测的级联和聚合变压器网络
PREAI
分享收藏
MEANet: An effective and lightweight solution for salient object detection in optical remote sensing imagesMEANet: 一种有效、轻量级的光学遥感图像显著目标检测解决方案
PREAI
分享收藏
查看更多内容