1 code implementation • 25 Nov 2021 • Sen yang, Zhicheng Wang, Ze Chen, YanJie Li, Shoukui Zhang, Zhibin Quan, Shu-Tao Xia, Yiping Bao, Erjin Zhou, Wankou Yang
This paper presents a new method to solve keypoint detection and instance association by using Transformer.
Ranked #10 on
Multi-Person Pose Estimation
on COCO test-dev
no code implementations • 22 Aug 2021 • Xiaohu Jiang, Ze Chen, Zhicheng Wang, Erjin Zhou, ChunYuan
After DETR was proposed, this novel transformer-based detection paradigm which performs several cross-attentions between object queries and feature maps for predictions has subsequently derived a series of transformer-based detection heads.
no code implementations • 22 Jul 2021 • Zhengxiong Luo, Zhicheng Wang, Yan Huang, Liang Wang, Tieniu Tan, Erjin Zhou
It can generate and fuse multi-scale features of the same spatial sizes by setting different dilation rates for different channels.
2 code implementations • 7 Jul 2021 • YanJie Li, Sen yang, Shoukui Zhang, Zhicheng Wang, Wankou Yang, Shu-Tao Xia, Erjin Zhou
The 2D heatmap representation has dominated human pose estimation for years due to its high performance.
1 code implementation • 8 Jun 2021 • Yang Hu, Haoxuan You, Zhecan Wang, Zhicheng Wang, Erjin Zhou, Yue Gao
Graph Neural Network (GNN) has been demonstrated its effectiveness in dealing with non-Euclidean structural data.
1 code implementation • ICCV 2021 • YanJie Li, Shoukui Zhang, Zhicheng Wang, Sen yang, Wankou Yang, Shu-Tao Xia, Erjin Zhou
Most existing CNN-based methods do well in visual representation, however, lacking in the ability to explicitly learn the constraint relationships between keypoints.
no code implementations • 7 Apr 2021 • Mingyang Shang, Dawei Xiang, Zhicheng Wang, Erjin Zhou
V2F-Net consists of two sub-networks: Visible region Detection Network (VDN) and Full body Estimation Network (FEN).
no code implementations • CVPR 2021 • Xing Dai, Zeren Jiang, Zhao Wu, Yiping Bao, Zhicheng Wang, Si Liu, Erjin Zhou
In recent years, knowledge distillation has been proved to be an effective solution for model compression.
1 code implementation • CVPR 2021 • Zhengxiong Luo, Zhicheng Wang, Yan Huang, Tieniu Tan, Erjin Zhou
However, for bottom-up methods, which need to handle a large variance of human scales and labeling ambiguities, the current practice seems unreasonable.
no code implementations • 13 Dec 2020 • Zhengxiong Luo, Zhicheng Wang, Yuanhao Cai, GuanAn Wang, Yan Huang, Liang Wang, Erjin Zhou, Tieniu Tan, Jian Sun
Instead, we focus on exploiting multi-scale information from layers with different receptive-field sizes and then making full of use this information by improving the fusion method.
1 code implementation • CVPR 2020 • Ling Yang, Liangliang Li, Zilun Zhang, Xinyu Zhou, Erjin Zhou, Yu Liu
To combine the distribution-level relations and instance-level relations for all examples, we construct a dual complete graph network which consists of a point graph and a distribution graph with each node standing for an example.
Ranked #1 on
Few-Shot Learning
on Mini-ImageNet - 1-Shot Learning
2 code implementations • CVPR 2020 • Guan'an Wang, Shuo Yang, Huanyu Liu, Zhicheng Wang, Yang Yang, Shuliang Wang, Gang Yu, Erjin Zhou, Jian Sun
When aligning two groups of local features from two images, we view it as a graph matching problem and propose a cross-graph embedded-alignment (CGEA) layer to jointly learn and embed topology information to local features, and straightly predict similarity score.
3 code implementations • ECCV 2020 • Yuanhao Cai, Zhicheng Wang, Zhengxiong Luo, Binyi Yin, Angang Du, Haoqian Wang, Xiangyu Zhang, Xinyu Zhou, Erjin Zhou, Jian Sun
To tackle this problem, we propose an efficient attention mechanism - Pose Refine Machine (PRM) to make a trade-off between local and global representations in output features and further refine the keypoint locations.
Ranked #1 on
Keypoint Detection
on COCO
no code implementations • ECCV 2018 • Erjin Zhou, Zhimin Cao, Jian Sun
In this paper, we propose a method, called GridFace, to reduce facial geometric variations and improve the recognition performance.
no code implementations • 16 Nov 2015 • Zhiao Huang, Erjin Zhou, Zhimin Cao
Facial landmark localization plays an important role in face recognition and analysis applications.
no code implementations • 20 Jan 2015 • Erjin Zhou, Zhimin Cao, Qi Yin
In this paper, we report our observations on how big data impacts the recognition performance.