297 citations · 1.3k across the 37 of their papers we have counts for
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The Devil is in the Details: Delving into Unbiased Data Processing for Human Pose Estimation
Junjie Huang, Zheng Zhu, Feng Guo +2
Being a fundamental component in training and inference, data processing has not been systematically considered in human pose estimation community, to the best of our knowledge. In…
Multi-Stage HRNet: Multiple Stage High-Resolution Network for Human Pose Estimation
Junjie Huang, Zheng Zhu, Guan Huang
Human pose estimation are of importance for visual understanding tasks such as action recognition and human-computer interaction. In this work, we present a Multiple Stage High-Res…
High Performance Visual Object Tracking with Unified Convolutional Networks
Zheng Zhu, Wei Zou, Guan Huang +2
Convolutional neural networks (CNN) based tracking approaches have shown favorable performance in recent benchmarks. Nonetheless, the chosen CNN features are always pre-trained in…
FastPose: Towards Real-time Pose Estimation and Tracking via Scale-normalized Multi-task Networks
Jiabin Zhang, Zheng Zhu, Wei Zou +4
Both accuracy and efficiency are significant for pose estimation and tracking in videos. State-of-the-art performance is dominated by two-stages top-down methods. Despite the leadi…
Instance Scale Normalization for image understanding
Zewen He, He Huang, Yudong Wu +2
Scale variation remains a challenging problem for object detection. Common paradigms usually adopt multiscale training & testing (image pyramid) or FPN (feature pyramid network) to…
State-aware Re-identification Feature for Multi-target Multi-camera Tracking
Peng Li, Jiabin Zhang, Zheng Zhu +3
Multi-target Multi-camera Tracking (MTMCT) aims to extract the trajectories from videos captured by a set of cameras. Recently, the tracking performance of MTMCT is significantly e…
Exploiting Offset-guided Network for Pose Estimation and Tracking
Rui Zhang, Zheng Zhu, Peng Li +4
Human pose estimation has witnessed a significant advance thanks to the development of deep learning. Recent human pose estimation approaches tend to directly predict the location…