3.5k citations · 16k across the 85 of their papers we have counts for
22 papers · 1 filter
Centralized Information Interaction for Salient Object Detection
Jiang-Jiang Liu, Zhi-Ang Liu, Ming-Ming Cheng
The U-shape structure has shown its advantage in salient object detection for efficiently combining multi-scale features. However, most existing U-shape based methods focused on im…
MobileSal: Extremely Efficient RGB-D Salient Object Detection
Yu-Huan Wu, Yun Liu, Jun Xu +3
The high computational cost of neural networks has prevented recent successes in RGB-D salient object detection (SOD) from benefiting real-world applications. Hence, this paper int…
EDN: Salient Object Detection via Extremely-Downsampled Network
Yu-Huan Wu, Yun Liu, Le Zhang +2
Recent progress on salient object detection (SOD) mainly benefits from multi-scale learning, where the high-level and low-level features collaborate in locating salient objects and…
Dense Attention Fluid Network for Salient Object Detection in Optical Remote Sensing Images
Qijian Zhang, Runmin Cong, Chongyi Li +5
Despite the remarkable advances in visual saliency analysis for natural scene images (NSIs), salient object detection (SOD) for optical remote sensing images (RSIs) still remains a…
Delving Deep into Label Smoothing
Chang-Bin Zhang, Peng-Tao Jiang, Qibin Hou +4
Label smoothing is an effective regularization tool for deep neural networks (DNNs), which generates soft labels by applying a weighted average between the uniform distribution and…
LID 2020: The Learning from Imperfect Data Challenge Results
Yunchao Wei, Shuai Zheng, Ming-Ming Cheng +32
Learning from imperfect data becomes an issue in many industrial applications after the research community has made profound progress in supervised learning from perfectly annotate…