Junliang Xing

Publications
Influence

The Visual Object Tracking VOT2016 Challenge Results

M. Kristan, A. Leonardis, +136 authors Zhizhen Chi
Computer Science
ECCV Workshops
8 October 2016

The Visual Object Tracking challenge VOT2016 aims at comparing short-term single-object visual trackers that do not apply pre-learned models of object appearance. Expand

SiamRPN++: Evolution of Siamese Visual Tracking With Very Deep Networks

B. Li, Wei Wu, Q. Wang, Fangyi Zhang, Junliang Xing, J. Yan
Computer Science
IEEE/CVF Conference on Computer Vision and…
31 December 2018

Siamese network based trackers formulate tracking as convolutional feature cross-correlation between target template and searching region. Expand

Transfer Learning Based Visual Tracking with Gaussian Processes Regression

Jin Gao, Haibin Ling, W. Hu, Junliang Xing
Computer Science
ECCV
6 September 2014

We propose a new transfer learning based visual tracker using Gaussian Processes Regression (GPR), and introduce a latent variable to assist the tracking decision. Expand

The Visual Object Tracking VOT2017 Challenge Results

M. Kristan, A. Leonardis, +101 authors Zhiqun He
Computer Science
IEEE International Conference on Computer Vision…
22 October 2017

The Visual Object Tracking challenge VOT2017 is the fifth annual tracker benchmarking activity organized by the VOT initiative. Expand

DCFNet: Discriminant Correlation Filters Network for Visual Tracking

Q. Wang, Jin Gao, Junliang Xing, Mengdan Zhang, W. Hu
Computer Science
ArXiv
13 April 2017

We present an end-to-end lightweight network architecture, namely DCFNet, to learn the convolutional features and perform the correlation tracking process simultaneously. Expand

An End-to-End Spatio-Temporal Attention Model for Human Action Recognition from Skeleton Data

Sijie Song, Cuiling Lan, Junliang Xing, Wenjun Zeng, Jiaying Liu
Computer Science
AAAI
18 November 2016

We propose an end-to-end spatial and temporal attention model for human action recognition from skeleton data. Expand

Co-Occurrence Feature Learning for Skeleton Based Action Recognition Using Regularized Deep LSTM Networks

Wentao Zhu, Cuiling Lan, +4 authors X. Xie
Computer Science
AAAI
12 February 2016

Skeleton based action recognition distinguishes human actions using the trajectories of skeleton joints, which provide a very good representation for describing actions. Expand

Pose-Driven Deep Convolutional Model for Person Re-identification

Chi Su, Jianing Li, S. Zhang, Junliang Xing, W. Gao, Q. Tian
Computer Science
IEEE International Conference on Computer Vision…
25 September 2017

We propose a Pose-driven Deep Convolutional (PDC) model to learn improved feature extraction and matching models from end to end. Expand

View Adaptive Recurrent Neural Networks for High Performance Human Action Recognition from Skeleton Data

Pengfei Zhang, Cuiling Lan, Junliang Xing, Wenjun Zeng, J. Xue, N. Zheng
Computer Science
IEEE International Conference on Computer Vision…
24 March 2017

We propose a view adaptive recurrent neural network with LSTM architecture, which enables the network itself to adapt to the most suitable observation viewpoints from end to end. Expand

A Deep Regression Architecture with Two-Stage Re-initialization for High Performance Facial Landmark Detection

Jiang-Jing Lv, Xiaohu Shao, Junliang Xing, C. Cheng, X. Zhou
Computer Science
IEEE Conference on Computer Vision and Pattern…
21 July 2017

In this paper, we present a deep regression architecture with two-stage re-initialization to explicitly deal with the initialization problem. Expand

Recommended Authors