Search Results for author: Jiagang Zhu

Found 13 papers, 2 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

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 +1

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 (training dataset metric)

Face Recognition Face Verification

Semi-Global Shape-aware Network

no code implementations17 Dec 2020 Pengju Zhang, Yihong Wu, Jiagang Zhu

In this paper, we propose a Semi-Global Shape-aware Network (SGSNet) considering both feature similarity and proximity for preserving object shapes when modeling long-range dependencies.

Computer Vision Image Retrieval +1

Multi-loss-aware Channel Pruning of Deep Networks

no code implementations27 Feb 2019 Yiming Hu, Siyang Sun, Jianquan Li, Jiagang Zhu, Xingang Wang, Qingyi Gu

Particularly, we introduce an additional loss to encode the differences in the feature and semantic distributions within feature maps between the baseline model and the pruned one.

General Classification

Cluster Regularized Quantization for Deep Networks Compression

no code implementations27 Feb 2019 Yiming Hu, Jianquan Li, Xianlei Long, Shenhua Hu, Jiagang Zhu, Xingang Wang, Qingyi Gu

Deep neural networks (DNNs) have achieved great success in a wide range of computer vision areas, but the applications to mobile devices is limited due to their high storage and computational cost.

Computer Vision Quantization

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

An Efficient Optical Flow Based Motion Detection Method for Non-stationary Scenes

no code implementations18 Nov 2018 Junjie Huang, Wei Zou, Zheng Zhu, Jiagang Zhu

Real-time motion detection in non-stationary scenes is a difficult task due to dynamic background, changing foreground appearance and limited computational resource.

Motion Detection Motion Detection In Non-Stationary Scenes +1

Optical Flow Based Online Moving Foreground Analysis

no code implementations18 Nov 2018 Junjie Huang, Wei Zou, Zheng Zhu, Jiagang Zhu

Obtained by moving object detection, the foreground mask result is unshaped and can not be directly used in most subsequent processes.

Moving Object Detection object-detection +1

Optical Flow Based Real-time Moving Object Detection in Unconstrained Scenes

no code implementations13 Jul 2018 Junjie Huang, Wei Zou, Jiagang Zhu, Zheng Zhu

Real-time moving object detection in unconstrained scenes is a difficult task due to dynamic background, changing foreground appearance and limited computational resource.

Moving Object Detection object-detection +1

End-to-end Video-level Representation Learning for Action Recognition

1 code implementation11 Nov 2017 Jiagang Zhu, Wei Zou, Zheng Zhu

From the frame/clip-level feature learning to the video-level representation building, deep learning methods in action recognition have developed rapidly in recent years.

Action Recognition Optical Flow Estimation +1

Learning Gating ConvNet for Two-Stream based Methods in Action Recognition

1 code implementation12 Sep 2017 Jiagang Zhu, Wei Zou, Zheng Zhu

For the two-stream style methods in action recognition, fusing the two streams' predictions is always by the weighted averaging scheme.

Action Classification Action Recognition +1

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