Search Results for author: Junliang Xing

Found 44 papers, 13 papers with code

RefineCap: Concept-Aware Refinement for Image Captioning

no code implementations8 Sep 2021 Yekun Chai, Shuo Jin, Junliang Xing

Automatically translating images to texts involves image scene understanding and language modeling.

Image Captioning Language Modelling +1

L2E: Learning to Exploit Your Opponent

no code implementations18 Feb 2021 Zhe Wu, Kai Li, Enmin Zhao, Hang Xu, Meng Zhang, Haobo Fu, Bo An, Junliang Xing

In this work, we propose a novel Learning to Exploit (L2E) framework for implicit opponent modeling.

Anti-UAV: A Large Multi-Modal Benchmark for UAV Tracking

1 code implementation21 Jan 2021 Nan Jiang, Kuiran Wang, Xiaoke Peng, Xuehui Yu, Qiang Wang, Junliang Xing, Guorong Li, Jian Zhao, Guodong Guo, Zhenjun Han

The releasing of such a large-scale dataset could be a useful initial step in research of tracking UAVs.

Temperature Regret Matching for Imperfect-Information Games

no code implementations1 Jan 2021 Enmin Zhao, Kai Li, Junliang Xing

Regret matching (RM) plays a crucial role in CFR and its variants to approach Nash equilibrium.

OpenHoldem: An Open Toolkit for Large-Scale Imperfect-Information Game Research

no code implementations11 Dec 2020 Kai Li, Hang Xu, Meng Zhang, Enmin Zhao, Zhe Wu, Junliang Xing, Kaiqi Huang

Owning to the unremitting efforts by a few institutes, significant progress has recently been made in designing superhuman AIs in No-limit Texas Hold'em (NLTH), the primary testbed for large-scale imperfect-information game research.

DSAM: A Distance Shrinking with Angular Marginalizing Loss for High Performance Vehicle Re-identificatio

no code implementations12 Nov 2020 Jiangtao Kong, Yu Cheng, Benjia Zhou, Kai Li, Junliang Xing

To obtain a high-performance vehicle ReID model, we present a novel Distance Shrinking with Angular Marginalizing (DSAM) loss function to perform hybrid learning in both the Original Feature Space (OFS) and the Feature Angular Space (FAS) using the local verification and the global identification information.

Person Re-Identification Vehicle Re-Identification

RDSNet: A New Deep Architecture for Reciprocal Object Detection and Instance Segmentation

1 code implementation11 Dec 2019 Shaoru Wang, Yongchao Gong, Junliang Xing, Lichao Huang, Chang Huang, Weiming Hu

To reciprocate these two tasks, we design a two-stream structure to learn features on both the object level (i. e., bounding boxes) and the pixel level (i. e., instance masks) jointly.

Instance Segmentation Object Detection +2

Relational Learning for Joint Head and Human Detection

no code implementations24 Sep 2019 Cheng Chi, Shifeng Zhang, Junliang Xing, Zhen Lei, Stan Z. Li, Xudong Zou

Head and human detection have been rapidly improved with the development of deep convolutional neural networks.

Head Detection Human Detection +1

PedHunter: Occlusion Robust Pedestrian Detector in Crowded Scenes

no code implementations15 Sep 2019 Cheng Chi, Shifeng Zhang, Junliang Xing, Zhen Lei, Stan Z. Li, Xudong Zou

Pedestrian detection in crowded scenes is a challenging problem, because occlusion happens frequently among different pedestrians.

Data Augmentation Occlusion Handling +2

Cross-Resolution Face Recognition via Prior-Aided Face Hallucination and Residual Knowledge Distillation

2 code implementations26 May 2019 Hanyang Kong, Jian Zhao, Xiaoguang Tu, Junliang Xing, ShengMei Shen, Jiashi Feng

Recent deep learning based face recognition methods have achieved great performance, but it still remains challenging to recognize very low-resolution query face like 28x28 pixels when CCTV camera is far from the captured subject.

Face Hallucination Face Recognition +2

Domain Adaptive Attention Model for Unsupervised Cross-Domain Person Re-Identification

no code implementations25 May 2019 Yangru Huang, Peixi Peng, Yi Jin, Junliang Xing, Congyan Lang, Songhe Feng

To reduce domain divergence caused by that the source and target datasets are collected from different environments, we force to project the DSH feature maps from different domains to a new nominal domain, and a novel domain similarity loss is proposed based on one-class classification.

Domain Adaptation General Classification +1

Multi-Prototype Networks for Unconstrained Set-based Face Recognition

no code implementations13 Feb 2019 Jian Zhao, Jianshu Li, Xiaoguang Tu, Fang Zhao, Yuan Xin, Junliang Xing, Hengzhu Liu, Shuicheng Yan, Jiashi Feng

In this paper, we study the challenging unconstrained set-based face recognition problem where each subject face is instantiated by a set of media (images and videos) instead of a single image.

Face Recognition

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

8 code implementations CVPR 2019 Bo Li, Wei Wu, Qiang Wang, Fangyi Zhang, Junliang Xing, Junjie Yan

Moreover, we propose a new model architecture to perform depth-wise and layer-wise aggregations, which not only further improves the accuracy but also reduces the model size.

Translation Visual Object Tracking +1

Cooperative Multi-Agent Policy Gradients with Sub-optimal Demonstration

no code implementations5 Dec 2018 Peixi Peng, Junliang Xing

To learn the multi-agent cooperation effectively and tackle the sub-optimality of demonstration, a self-improving learning method is proposed: On the one hand, the centralized state-action values are initialized by the demonstration and updated by the learned decentralized policy to improve the sub-optimality.

Representation based and Attention augmented Meta learning

no code implementations19 Nov 2018 Yunxiao Qin, Chenxu Zhao, Zezheng Wang, Junliang Xing, Jun Wan, Zhen Lei

The method RAML aims to give the Meta learner the ability of leveraging the past learned knowledge to reduce the dimension of the original input data by expressing it into high representations, and help the Meta learner to perform well.

Few-Shot Learning

Temporal-Spatial Mapping for Action Recognition

no code implementations11 Sep 2018 Xiaolin Song, Cuiling Lan, Wen-Jun Zeng, Junliang Xing, Jingyu Yang, Xiaoyan Sun

We propose a video level 2D feature representation by transforming the convolutional features of all frames to a 2D feature map, referred to as VideoMap.

Action Recognition Image Classification +1

Selective Refinement Network for High Performance Face Detection

3 code implementations7 Sep 2018 Cheng Chi, Shifeng Zhang, Junliang Xing, Zhen Lei, Stan Z. Li, Xudong Zou

In particular, the SRN consists of two modules: the Selective Two-step Classification (STC) module and the Selective Two-step Regression (STR) module.

Face Detection General Classification

Visual Tracking via Spatially Aligned Correlation Filters Network

no code implementations ECCV 2018 Mengdan Zhang, Qiang Wang, Junliang Xing, Jin Gao, Peixi Peng, Weiming Hu, Steve Maybank

Correlation filters based trackers rely on a periodic assumption of the search sample to efficiently distinguish the target from the background.

Visual Tracking

Pose Partition Networks for Multi-Person Pose Estimation

no code implementations ECCV 2018 Xuecheng Nie, Jiashi Feng, Junliang Xing, Shuicheng Yan

This paper proposes a novel Pose Partition Network (PPN) to address the challenging multi-person pose estimation problem.

Human Detection Multi-Person Pose Estimation

Learning Attentions: Residual Attentional Siamese Network for High Performance Online Visual Tracking

2 code implementations CVPR 2018 Qiang Wang, Zhu Teng, Junliang Xing, Jin Gao, Weiming Hu, Stephen Maybank

The RASNet model reformulates the correlation filter within a Siamese tracking framework, and introduces different kinds of the attention mechanisms to adapt the model without updating the model online.

Object Tracking Representation Learning +1

Deep Cost-Sensitive and Order-Preserving Feature Learning for Cross-Population Age Estimation

no code implementations CVPR 2018 Kai Li, Junliang Xing, Chi Su, Weiming Hu, Yundong Zhang, Stephen Maybank

First, a novel cost-sensitive multi-task loss function is designed to learn transferable aging features by training on the source population.

Age Estimation

View Adaptive Neural Networks for High Performance Skeleton-based Human Action Recognition

2 code implementations20 Apr 2018 Pengfei Zhang, Cuiling Lan, Junliang Xing, Wen-Jun Zeng, Jianru Xue, Nanning Zheng

In order to alleviate the effects of view variations, this paper introduces a novel view adaptation scheme, which automatically determines the virtual observation viewpoints in a learning based data driven manner.

Action Recognition Skeleton Based Action Recognition

Pose-driven Deep Convolutional Model for Person Re-identification

no code implementations ICCV 2017 Chi Su, Jianing Li, Shiliang Zhang, Junliang Xing, Wen Gao, Qi Tian

Our deep architecture explicitly leverages the human part cues to alleviate the pose variations and learn robust feature representations from both the global image and different local parts.

Person Re-Identification

Human Pose Estimation using Global and Local Normalization

no code implementations ICCV 2017 Ke Sun, Cuiling Lan, Junliang Xing, Wen-Jun Zeng, Dong Liu, Jingdong Wang

We present a two-stage normalization scheme, human body normalization and limb normalization, to make the distribution of the relative joint locations compact, resulting in easier learning of convolutional spatial models and more accurate pose estimation.

Pose Estimation

A Deep Regression Architecture With Two-Stage Re-Initialization for High Performance Facial Landmark Detection

1 code implementation CVPR 2017 Jiangjing Lv, Xiaohu Shao, Junliang Xing, Cheng Cheng, Xi Zhou

At the global stage, given an image with a rough face detection result, the full face region is firstly re-initialized by a supervised spatial transformer network to a canonical shape state and then trained to regress a coarse landmark estimation.

Face Detection Facial Landmark Detection

Generative Partition Networks for Multi-Person Pose Estimation

1 code implementation21 May 2017 Xuecheng Nie, Jiashi Feng, Junliang Xing, Shuicheng Yan

This paper proposes a new Generative Partition Network (GPN) to address the challenging multi-person pose estimation problem.

 Ranked #1 on Multi-Person Pose Estimation on WAF (AP metric)

Human Detection Keypoint Detection +1

DCFNet: Discriminant Correlation Filters Network for Visual Tracking

5 code implementations13 Apr 2017 Qiang Wang, Jin Gao, Junliang Xing, Mengdan Zhang, Weiming Hu

In this work, we present an end-to-end lightweight network architecture, namely DCFNet, to learn the convolutional features and perform the correlation tracking process simultaneously.

Object Tracking Visual Tracking

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

no code implementations ICCV 2017 Pengfei Zhang, Cuiling Lan, Junliang Xing, Wen-Jun Zeng, Jianru Xue, Nanning Zheng

Rather than re-positioning the skeletons based on a human defined prior criterion, we design a view adaptive recurrent neural network (RNN) with LSTM architecture, which enables the network itself to adapt to the most suitable observation viewpoints from end to end.

Action Recognition Skeleton Based Action Recognition

A Graphical Social Topology Model for Multi-Object Tracking

no code implementations14 Feb 2017 Shan Gao, Xiaogang Chen, Qixiang Ye, Junliang Xing, Arjan Kuijper, Xiangyang Ji

Inspired with the social affinity property of moving objects, we propose a Graphical Social Topology (GST) model, which estimates the group dynamics by jointly modeling the group structure and the states of objects using a topological representation.

Multi-Object Tracking

Tensor Power Iteration for Multi-Graph Matching

no code implementations CVPR 2016 Xinchu Shi, Haibin Ling, Weiming Hu, Junliang Xing, Yanning Zhang

Due to its wide range of applications, matching between two graphs has been extensively studied and remains an active topic.

Graph Matching

Deep Attributes Driven Multi-Camera Person Re-identification

no code implementations11 May 2016 Chi Su, Shiliang Zhang, Junliang Xing, Wen Gao, Qi Tian

And we propose a semi-supervised attribute learning framework which progressively boosts the accuracy of attributes only using a limited number of labeled data.

Metric Learning Person Re-Identification

Co-occurrence Feature Learning for Skeleton based Action Recognition using Regularized Deep LSTM Networks

no code implementations24 Mar 2016 Wentao Zhu, Cuiling Lan, Junliang Xing, Wen-Jun Zeng, Yanghao Li, Li Shen, Xiaohui Xie

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

Action Recognition Skeleton Based Action Recognition

Local Subspace Collaborative Tracking

no code implementations ICCV 2015 Lin Ma, Xiaoqin Zhang, Weiming Hu, Junliang Xing, Jiwen Lu, Jie zhou

To address this, this paper presents a local subspace collaborative tracking method for robust visual tracking, where multiple linear and nonlinear subspaces are learned to better model the nonlinear relationship of object appearances.

Object Tracking Visual Tracking

Shape Driven Kernel Adaptation in Convolutional Neural Network for Robust Facial Traits Recognition

no code implementations CVPR 2015 Shaoxin Li, Junliang Xing, Zhiheng Niu, Shiguang Shan, Shuicheng Yan

Comprehensive experiments on WebFace, Morph II and MultiPIE databases well validate the effectiveness of the proposed kernel adaptation method and tree-structured convolutional architecture for facial traits recognition tasks, including identity, age and gender classification.

Age And Gender Classification

Multiple Object Tracking: A Literature Review

no code implementations26 Sep 2014 Wenhan Luo, Junliang Xing, Anton Milan, Xiaoqin Zhang, Wei Liu, Xiaowei Zhao, Tae-Kyun Kim

We inspect the recent advances in various aspects and propose some interesting directions for future research.

Multiple Object Tracking

Towards Multi-view and Partially-Occluded Face Alignment

no code implementations CVPR 2014 Junliang Xing, Zhiheng Niu, Junshi Huang, Weiming Hu, Shuicheng Yan

During each training stage, the SRD model learns a relational dictionary to capture consistent relationships between face appearance and shape, which are respectively modeled by the pose-indexed image features and the shape displacements for current estimated landmarks.

Face Alignment

Multi-target Tracking with Motion Context in Tensor Power Iteration

no code implementations CVPR 2014 Xinchu Shi, Haibin Ling, Weiming Hu, Chunfeng Yuan, Junliang Xing

In this paper, we model interactions between neighbor targets by pair-wise motion context, and further encode such context into the global association optimization.

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