80 citations · 137 across the 8 of their papers we have counts for
8 papers
SSR-HEF: Crowd Counting with Multi-Scale Semantic Refining and Hard Example Focusing
Jiwei Chen, Kewei Wang, Wen Su +1
Crowd counting based on density maps is generally regarded as a regression task.Deep learning is used to learn the mapping between image content and crowd density distribution. Alt…
Crowd counting with segmentation attention convolutional neural network
Jiwei Chen, Zengfu Wang
Deep learning occupies an undisputed dominance in crowd counting. In this paper, we propose a novel convolutional neural network (CNN) architecture called SegCrowdNet. Despite the…
Crowd counting with crowd attention convolutional neural network
Jiwei Chen, Wen Su, Zengfu Wang
Crowd counting is a challenging problem due to the scene complexity and scale variation. Although deep learning has achieved great improvement in crowd counting, scene complexity a…
On Exploring and Improving Robustness of Scene Text Detection Models
Shilian Wu, Wei Zhai, Yongrui Li +2
It is crucial to understand the robustness of text detection models with regard to extensive corruptions, since scene text detection techniques have many practical applications. Fo…
Greedy Offset-Guided Keypoint Grouping for Human Pose Estimation
Jia Li, Linhua Xiang, Jiwei Chen +1
We propose a simple yet reliable bottom-up approach with a good trade-off between accuracy and efficiency for the problem of multi-person pose estimation. Given an image, we employ…
Simple Pose: Rethinking and Improving a Bottom-up Approach for Multi-Person Pose Estimation
Jia Li, Wen Su, Zengfu Wang
We rethink a well-know bottom-up approach for multi-person pose estimation and propose an improved one. The improved approach surpasses the baseline significantly thanks to (1) an…
Grand Challenge of 106-Point Facial Landmark Localization
Yinglu Liu, Hao Shen, Yue Si +18
Facial landmark localization is a very crucial step in numerous face related applications, such as face recognition, facial pose estimation, face image synthesis, etc. However, pre…
Nighttime Haze Removal with Illumination Correction
Jing Zhang, Yang Cao, Zengfu Wang
Haze removal is important for computational photography and computer vision applications. However, most of the existing methods for dehazing are designed for daytime images, and ca…