297 citations · 739 across the 19 of their papers we have counts for
19 papers
BEVPoolv2: A Cutting-edge Implementation of BEVDet Toward Deployment
Junjie Huang, Guan Huang
We release a new codebase version of the BEVDet, dubbed branch dev2.0. With dev2.0, we propose BEVPoolv2 upgrade the view transformation process from the perspective of engineering…
BEVerse: Unified Perception and Prediction in Birds-Eye-View for Vision-Centric Autonomous Driving
Yunpeng Zhang, Zheng Zhu, Wenzhao Zheng +4
In this paper, we present BEVerse, a unified framework for 3D perception and prediction based on multi-camera systems. Unlike existing studies focusing on the improvement of single…
Gait Recognition in the Wild: A Large-scale Benchmark and NAS-based Baseline
Xianda Guo, Zheng Zhu, Tian Yang +6
Gait benchmarks empower the research community to train and evaluate high-performance gait recognition systems. Even though growing efforts have been devoted to cross-view recognit…
WebFace260M: A Benchmark for Million-Scale Deep Face Recognition
Zheng Zhu, Guan Huang, Jiankang Deng +8
Face benchmarks empower the research community to train and evaluate high-performance face recognition systems. In this paper, we contribute a new million-scale recognition benchma…
HFT: Lifting Perspective Representations via Hybrid Feature Transformation
Jiayu Zou, Junrui Xiao, Zheng Zhu +4
Autonomous driving requires accurate and detailed Bird's Eye View (BEV) semantic segmentation for decision making, which is one of the most challenging tasks for high-level scene p…
BEVDet4D: Exploit Temporal Cues in Multi-camera 3D Object Detection
Junjie Huang, Guan Huang
Single frame data contains finite information which limits the performance of the existing vision-based multi-camera 3D object detection paradigms. For fundamentally pushing the pe…
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…
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 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…
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…
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…
Compensation Tracker: Reprocessing Lost Object for Multi-Object Tracking
Zhibo Zou, Junjie Huang, Ping Luo
Tracking by detection paradigm is one of the most popular object tracking methods. However, it is very dependent on the performance of the detector. When the detector has a behavio…
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…
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…
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…
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…
Optical Flow Based Online Moving Foreground Analysis
Junjie Huang, Wei Zou, Zheng Zhu +1
Obtained by moving object detection, the foreground mask result is unshaped and can not be directly used in most subsequent processes. In this paper, we focus on this problem and a…
Optical Flow Based Real-time Moving Object Detection in Unconstrained Scenes
Junjie Huang, Wei Zou, Jiagang Zhu +1
Real-time moving object detection in unconstrained scenes is a difficult task due to dynamic background, changing foreground appearance and limited computational resource. In this…