1 code implementation • 8 Mar 2022 • Shikun Li, Xiaobo Xia, Shiming Ge, Tongliang Liu
In the selection process, by measuring the agreement between learned representations and given labels, we first identify confident examples that are exploited to build confident pairs.
Ranked #8 on
Image Classification
on mini WebVision 1.0
1 code implementation • 8 Mar 2022 • Shikun Li, Tongliang Liu, Jiyong Tan, Dan Zeng, Shiming Ge
This raises the following important question: how can we effectively use a small amount of trusted data to facilitate robust classifier learning from multiple annotators?
1 code implementation • 19 Jan 2022 • Chunhui Zhang, Guanjie Huang, Li Liu, Shan Huang, Yinan Yang, Yuxuan Zhang, Xiang Wan, Shiming Ge
In this work, we contribute a new million-scale Unmanned Aerial Vehicle (UAV) tracking benchmark, called WebUAV-3M.
no code implementations • 29 Sep 2021 • Chaojian Yu, Bo Han, Mingming Gong, Li Shen, Shiming Ge, Bo Du, Tongliang Liu
In this paper, we propose such a criterion, namely Loss Stationary Condition (LSC) for constrained perturbation.
no code implementations • 23 Aug 2021 • Jian Zhao, Gang Wang, Jianan Li, Lei Jin, Nana Fan, Min Wang, Xiaojuan Wang, Ting Yong, Yafeng Deng, Yandong Guo, Shiming Ge, Guodong Guo
The 2nd Anti-UAV Workshop \& Challenge aims to encourage research in developing novel and accurate methods for multi-scale object tracking.
no code implementations • 21 Jun 2021 • Yingying Hua, Daichi Zhang, Pengju Wang, Shiming Ge
The approach could make the face manipulation detection process transparent by embedding the feature whitening module.
no code implementations • 23 Mar 2021 • Kangkai Zhang, Chunhui Zhang, Shikun Li, Dan Zeng, Shiming Ge
Inspired by that, we propose an evolutionary knowledge distillation approach to improve the transfer effectiveness of teacher knowledge.
no code implementations • 31 Aug 2020 • Guanshuo Wang, Yufeng Yuan, Jiwei Li, Shiming Ge, Xi Zhou
Current stripe-based feature learning approaches have delivered impressive accuracy, but do not make a proper trade-off between diversity, locality, and robustness, which easily suffers from part semantic inconsistency for the conflict between rigid partition and misalignment.
no code implementations • 9 Mar 2020 • Jialin Gao, Zhixiang Shi, Jiani Li, Guanshuo Wang, Yufeng Yuan, Shiming Ge, Xi Zhou
Accurate temporal action proposals play an important role in detecting actions from untrimmed videos.
no code implementations • 24 Dec 2019 • Jialin Gao, Tong He, Xi Zhou, Shiming Ge
A collection of approaches based on graph convolutional networks have proven success in skeleton-based action recognition by exploring neighborhood information and dense dependencies between intra-frame joints.
Ranked #19 on
Skeleton Based Action Recognition
on NTU RGB+D
2 code implementations • 11 Jul 2019 • Xin Jin, Le Wu, Geng Zhao, Xiao-Dong Li, Xiaokun Zhang, Shiming Ge, Dongqing Zou, Bin Zhou, Xinghui Zhou
This is a new formula of image aesthetic assessment, which predicts aesthetic attributes captions together with the aesthetic score of each attribute.
no code implementations • 10 Apr 2019 • Jia Li, Kui Fu, Shengwei Zhao, Shiming Ge
In this approach, five components are involved, including two teachers, two students and the desired spatiotemporal model.
no code implementations • 9 Apr 2019 • Kui Fu, Peipei Shi, Yafei Song, Shiming Ge, Xiangju Lu, Jia Li
To address these issues, we design an extremely light-weight network with ultrafast speed, named UVA-Net.
no code implementations • 25 Nov 2018 • Shiming Ge, Shengwei Zhao, Chenyu Li, Jia Li
In this approach, a two-stream convolutional neural network (CNN) is first initialized to recognize high-resolution faces and resolution-degraded faces with a teacher stream and a student stream, respectively.
2 code implementations • 23 Aug 2017 • Xin Jin, Le Wu, Xiao-Dong Li, Siyu Chen, Siwei Peng, Jingying Chi, Shiming Ge, Chenggen Song, Geng Zhao
Thus, a novel CNN based on the Cumulative distribution with Jensen-Shannon divergence (CJS-CNN) is presented to predict the aesthetic score distribution of human ratings, with a new reliability-sensitive learning method based on the kurtosis of the score distribution, which eliminates the requirement of the original full data of human ratings (without normalization).
no code implementations • 23 Aug 2017 • Xin Jin, Yannan Li, Ningning Liu, Xiao-Dong Li, Xianggang Jiang, Chaoen Xiao, Shiming Ge
We propose a novel outdoor scene relighting method, which needs only a single reference image and is based on material constrained layer decomposition.
no code implementations • 9 Aug 2017 • Xin Jin, Shiming Ge, Chenggen Song
The experimental results reveal that our protocol can successfully retrieve the proper photos from the cloud server and protect the user photos and the face detector.
no code implementations • CVPR 2017 • Shiming Ge, Jia Li, Qiting Ye, Zhao Luo
Detecting masked faces (i. e., faces with occlusions) is a challenging task due to two main reasons: 1)the absence of large datasets of masked faces, and 2)the absence of facial cues from the masked regions.
no code implementations • 27 Feb 2017 • Xin Jin, Peng Yuan, Xiao-Dong Li, Chenggen Song, Shiming Ge, Geng Zhao, Yingya Chen
Only the base images are submitted randomly to the cloud server.
2 code implementations • 7 Oct 2016 • Xin Jin, Le Wu, Xiao-Dong Li, Xiaokun Zhang, Jingying Chi, Siwei Peng, Shiming Ge, Geng Zhao, Shuying Li
Thus, it is easy to use a pre-trained GoogLeNet for large-scale image classification problem and fine tune our connected layers on an large scale database of aesthetic related images: AVA, i. e. \emph{domain adaptation}.