activity
20162019
most citedCost-Effective Active Learning for Deep Image Classification

676 citations · 694 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV201910 cited

Adaptively Connected Neural Networks

Guangrun Wang, Keze Wang, Liang Lin

This paper presents a novel adaptively connected neural network (ACNet) to improve the traditional convolutional neural networks (CNNs) {in} two aspects. First, ACNet employs a fle…

cs.CV20192 cited

3D Human Pose Machines with Self-supervised Learning

Keze Wang, Liang Lin, Chenhan Jiang +2

Driven by recent computer vision and robotic applications, recovering 3D human poses has become increasingly important and attracted growing interests. In fact, completing this tas…

cs.CV2017676 cited

Cost-Effective Active Learning for Deep Image Classification

Keze Wang, Dongyu Zhang, Ya Li +2

Recent successes in learning-based image classification, however, heavily rely on the large number of annotated training samples, which may require considerable human efforts. In t…

cs.CV20164 cited

Human Pose Estimation from Depth Images via Inference Embedded Multi-task Learning

Keze Wang, Shengfu Zhai, Hui Cheng +2

Human pose estimation (i.e., locating the body parts / joints of a person) is a fundamental problem in human-computer interaction and multimedia applications. Significant progress…

cs.CV20162 cited

Local- and Holistic- Structure Preserving Image Super Resolution via Deep Joint Component Learning

Yukai Shi, Keze Wang, Li Xu +1

Recently, machine learning based single image super resolution (SR) approaches focus on jointly learning representations for high-resolution (HR) and low-resolution (LR) image patc…