297 citations · 799 across the 32 of their papers we have counts for
32 papers
BEVDet: High-performance Multi-camera 3D Object Detection in Bird-Eye-View
Junjie Huang, Guan Huang, Zheng Zhu +2
Autonomous driving perceives its surroundings for decision making, which is one of the most complex scenarios in visual perception. The success of paradigm innovation in solving th…
DenseCLIP: Language-Guided Dense Prediction with Context-Aware Prompting
Yongming Rao, Wenliang Zhao, Guangyi Chen +5
Recent progress has shown that large-scale pre-training using contrastive image-text pairs can be a promising alternative for high-quality visual representation learning from natur…
Face-NMS: A Core-set Selection Approach for Efficient Face Recognition
Yunze Chen, Junjie Huang, Jiagang Zhu +4
Recently, face recognition in the wild has achieved remarkable success and one key engine is the increasing size of training data. For example, the largest face dataset, WebFace42M…
Masked Face Recognition Challenge: The InsightFace Track Report
Jiankang Deng, Jia Guo, Xiang An +2
During the COVID-19 coronavirus epidemic, almost everyone wears a facial mask, which poses a huge challenge to deep face recognition. In this workshop, we organize Masked Face Reco…
Masked Face Recognition Challenge: The WebFace260M Track Report
Zheng Zhu, Guan Huang, Jiankang Deng +9
According to WHO statistics, there are more than 204,617,027 confirmed COVID-19 cases including 4,323,247 deaths worldwide till August 12, 2021. During the coronavirus epidemic, al…
Global Filter Networks for Image Classification
Yongming Rao, Wenliang Zhao, Zheng Zhu +2
Recent advances in self-attention and pure multi-layer perceptrons (MLP) models for vision have shown great potential in achieving promising performance with fewer inductive biases…
An Efficient Training Approach for Very Large Scale Face Recognition
Kai Wang, Shuo Wang, Panpan Zhang +7
Face recognition has achieved significant progress in deep learning era due to the ultra-large-scale and welllabeled datasets. However, training on the outsize datasets is time-con…
SIMPLE: SIngle-network with Mimicking and Point Learning for Bottom-up Human Pose Estimation
Jiabin Zhang, Zheng Zhu, Jiwen Lu +3
The practical application requests both accuracy and efficiency on multi-person pose estimation algorithms. But the high accuracy and fast inference speed are dominated by top-down…
Structure-Aware Face Clustering on a Large-Scale Graph with Nodes
Shuai Shen, Wanhua Li, Zheng Zhu +4
Face clustering is a promising method for annotating unlabeled face images. Recent supervised approaches have boosted the face clustering accuracy greatly, however their performanc…
WebFace260M: A Benchmark Unveiling the Power of Million-Scale Deep Face Recognition
Zheng Zhu, Guan Huang, Jiankang Deng +8
In this paper, we contribute a new million-scale face benchmark containing noisy 4M identities/260M faces (WebFace260M) and cleaned 2M identities/42M faces (WebFace42M) training da…
AID: Pushing the Performance Boundary of Human Pose Estimation with Information Dropping Augmentation
Junjie Huang, Zheng Zhu, Guan Huang +1
Both appearance cue and constraint cue are vital for human pose estimation. However, there is a tendency in most existing works to overfitting the former and overlook the latter. I…
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…
Predicting origin-destination ride-sourcing demand with a spatio-temporal encoder-decoder residual multi-graph convolutional network
Jintao Ke, Xiaoran Qin, Hai Yang +3
With the rapid development of mobile-internet technologies, on-demand ride-sourcing services have become increasingly popular and largely reshaped the way people travel. Demand pre…
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…
Human Following for Wheeled Robot with Monocular Pan-tilt Camera
Zheng Zhu, Hongxuan Ma, Wei Zou
Human following on mobile robots has witnessed significant advances due to its potentials for real-world applications. Currently most human following systems are equipped with dept…
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…
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…
Action Machine: Rethinking Action Recognition in Trimmed Videos
Jiagang Zhu, Wei Zou, Liang Xu +6
Existing methods in video action recognition mostly do not distinguish human body from the environment and easily overfit the scenes and objects. In this work, we present a concept…
Identity-Enhanced Network for Facial Expression Recognition
Yanwei Li, Xingang Wang, Shilei Zhang +4
Facial expression recognition is a challenging task, arguably because of large intra-class variations and high inter-class similarities. The core drawback of the existing approache…
Attention-guided Unified Network for Panoptic Segmentation
Yanwei Li, Xinze Chen, Zheng Zhu +4
This paper studies panoptic segmentation, a recently proposed task which segments foreground (FG) objects at the instance level as well as background (BG) contents at the semantic…
Multi-hierarchical Independent Correlation Filters for Visual Tracking
Shuai Bai, Zhiqun He, Ting-Bing Xu +3
For visual tracking, most of the traditional correlation filters (CF) based methods suffer from the bottleneck of feature redundancy and lack of motion information. In this paper,…
An Efficient Optical Flow Based Motion Detection Method for Non-stationary Scenes
Junjie Huang, Wei Zou, Zheng Zhu +1
Real-time motion detection in non-stationary scenes is a difficult task due to dynamic background, changing foreground appearance and limited computational resource. These challeng…