Search Results for author: Dalong Du

Found 17 papers, 7 papers with code

WebFace260M: A Benchmark for Million-Scale Deep Face Recognition

no code implementations21 Apr 2022 Zheng Zhu, Guan Huang, Jiankang Deng, Yun Ye, JunJie Huang, Xinze Chen, Jiagang Zhu, Tian Yang, Dalong Du, Jiwen Lu, Jie zhou

For a comprehensive evaluation of face matchers, three recognition tasks are performed under standard, masked and unbiased settings, respectively.

Face Recognition

HFT: Lifting Perspective Representations via Hybrid Feature Transformation

1 code implementation11 Apr 2022 Jiayu Zou, Junrui Xiao, Zheng Zhu, JunJie Huang, Guan Huang, Dalong Du, Xingang Wang

In order to reap the benefits and avoid the drawbacks of CBFT and CFFT, we propose a novel framework with a Hybrid Feature Transformation module (HFT).

Autonomous Driving Decision Making +1

Face-NMS: A Core-set Selection Approach for Efficient Face Recognition

no code implementations10 Sep 2021 Yunze Chen, JunJie Huang, Jiagang Zhu, Zheng Zhu, Tian Yang, Guan Huang, Dalong Du

The current research on this problem mainly focuses on designing an efficient Fully-connected layer (FC) to reduce GPU memory consumption caused by a large number of identities.

Face Recognition Object Detection

Structure-Aware Face Clustering on a Large-Scale Graph With 107 Nodes

1 code implementation CVPR 2021 Shuai Shen, Wanhua Li, Zheng Zhu, Guan Huang, Dalong Du, Jiwen Lu, Jie zhou

To address the dilemma of large-scale training and efficient inference, we propose the STructure-AwaRe Face Clustering (STAR-FC) method.

Face Clustering Graph Clustering

Structure-Aware Face Clustering on a Large-Scale Graph with $\bf{10^{7}}$ Nodes

no code implementations24 Mar 2021 Shuai Shen, Wanhua Li, Zheng Zhu, Guan Huang, Dalong Du, Jiwen Lu, Jie zhou

To address the dilemma of large-scale training and efficient inference, we propose the STructure-AwaRe Face Clustering (STAR-FC) method.

Face Clustering Graph Clustering

WebFace260M: A Benchmark Unveiling the Power of Million-Scale Deep Face Recognition

no code implementations CVPR 2021 Zheng Zhu, Guan Huang, Jiankang Deng, Yun Ye, JunJie Huang, Xinze Chen, Jiagang Zhu, Tian Yang, Jiwen Lu, Dalong Du, Jie zhou

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 data, as well as an elaborately designed time-constrained evaluation protocol.

 Ranked #1 on Face Verification on IJB-C (dataset metric)

Face Recognition Face Verification

AID: Pushing the Performance Boundary of Human Pose Estimation with Information Dropping Augmentation

2 code implementations17 Aug 2020 Junjie Huang, Zheng Zhu, Guan Huang, Dalong Du

As AID successfully pushes the performance boundary of human pose estimation problem by considerable margin and sets a new state-of-the-art, we hope AID to be a regular configuration for training human pose estimators.

Multi-Person Pose Estimation

The Devil is in the Details: Delving into Unbiased Data Processing for Human Pose Estimation

2 code implementations CVPR 2020 Junjie Huang, Zheng Zhu, Feng Guo, Guan Huang, Dalong Du

Specifically, by investigating the standard data processing in state-of-the-art approaches mainly including coordinate system transformation and keypoint format transformation (i. e., encoding and decoding), we find that the results obtained by common flipping strategy are unaligned with the original ones in inference.

Pose Estimation

High Performance Visual Object Tracking with Unified Convolutional Networks

no code implementations26 Aug 2019 Zheng Zhu, Wei Zou, Guan Huang, Dalong Du, Chang Huang

In this paper, we propose an end-to-end framework to learn the convolutional features and perform the tracking process simultaneously, namely, a unified convolutional tracker (UCT).

Visual Object Tracking

Action Machine: Rethinking Action Recognition in Trimmed Videos

no code implementations14 Dec 2018 Jiagang Zhu, Wei Zou, Liang Xu, Yiming Hu, Zheng Zhu, Manyu Chang, Jun-Jie Huang, Guan Huang, Dalong Du

On NTU RGB-D, Action Machine achieves the state-of-the-art performance with top-1 accuracies of 97. 2% and 94. 3% on cross-view and cross-subject respectively.

Action Recognition Multimodal Activity Recognition +2

Attention-guided Unified Network for Panoptic Segmentation

no code implementations CVPR 2019 Yanwei Li, Xinze Chen, Zheng Zhu, Lingxi Xie, Guan Huang, Dalong Du, Xingang Wang

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 level.

Panoptic Segmentation

UCT: Learning Unified Convolutional Networks for Real-time Visual Tracking

no code implementations10 Nov 2017 Zheng Zhu, Guan Huang, Wei Zou, Dalong Du, Chang Huang

Convolutional neural networks (CNN) based tracking approaches have shown favorable performance in recent benchmarks.

Real-Time Visual Tracking

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