Search Results for author: Jian Zhao

Found 59 papers, 25 papers with code

Unsupervised Domain Adaptation with Noise Resistible Mutual-Training for Person Re-identification

no code implementations ECCV 2020 Fang Zhao, Shengcai Liao, Guo-Sen Xie, Jian Zhao, Kaihao Zhang, Ling Shao

On the other hand, mutual instance selection further selects reliable and informative instances for training according to the peer-confidence and relationship disagreement of the networks.

Person Re-Identification Unsupervised Domain Adaptation

RandomMix: A mixed sample data augmentation method with multiple mixed modes

no code implementations18 May 2022 Xiaoliang Liu, Furao Shen, Jian Zhao, Changhai Nie

Data augmentation is a very practical technique that can be used to improve the generalization ability of neural networks and prevent overfitting.

Data Augmentation

Multi-Target Active Object Tracking with Monte Carlo Tree Search and Target Motion Modeling

no code implementations7 May 2022 Zheng Chen, Jian Zhao, Mingyu Yang, Wengang Zhou, Houqiang Li

In this work, we are dedicated to multi-target active object tracking (AOT), where there are multiple targets as well as multiple cameras in the environment.

Multi-agent Reinforcement Learning Object Tracking

LDSA: Learning Dynamic Subtask Assignment in Cooperative Multi-Agent Reinforcement Learning

no code implementations5 May 2022 Mingyu Yang, Jian Zhao, Xunhan Hu, Wengang Zhou, Jiangcheng Zhu, Houqiang Li

In this way, agents dealing with the same subtask share their learning of specific abilities and different subtasks correspond to different specific abilities.

Multi-agent Reinforcement Learning reinforcement-learning +2

Infographics Wizard: Flexible Infographics Authoring and Design Exploration

1 code implementation21 Apr 2022 Anjul Tyagi, Jian Zhao, Pushkar Patel, Swasti Khurana, Klaus Mueller

With the help of designers, we propose a semi-automated infographic framework for general structured and flow-based infographic design generation.

Image Data Augmentation for Deep Learning: A Survey

no code implementations19 Apr 2022 Suorong Yang, Weikang Xiao, Mengcheng Zhang, Suhan Guo, Jian Zhao, Furao Shen

By improving the quantity and diversity of training data, data augmentation has become an inevitable part of deep learning model training with image data.

Data Augmentation Image Classification +2

DouZero+: Improving DouDizhu AI by Opponent Modeling and Coach-guided Learning

1 code implementation6 Apr 2022 Youpeng Zhao, Jian Zhao, Xunhan Hu, Wengang Zhou, Houqiang Li

Recent years have witnessed the great breakthrough of deep reinforcement learning (DRL) in various perfect and imperfect information games.

Thin-Plate Spline Motion Model for Image Animation

1 code implementation27 Mar 2022 Jian Zhao, HUI ZHANG

Firstly, we propose thin-plate spline motion estimation to produce a more flexible optical flow, which warps the feature maps of the source image to the feature domain of the driving image.

Image Animation Motion Estimation +1

AutoAdversary: A Pixel Pruning Method for Sparse Adversarial Attack

no code implementations18 Mar 2022 Jinqiao Li, Xiaotao Liu, Jian Zhao, Furao Shen

A special branch of adversarial examples, namely sparse adversarial examples, can fool the target DNNs by perturbing only a few pixels.

Adversarial Attack Network Pruning

CTDS: Centralized Teacher with Decentralized Student for Multi-Agent Reinforcement Learning

1 code implementation16 Mar 2022 Jian Zhao, Xunhan Hu, Mingyu Yang, Wengang Zhou, Jiangcheng Zhu, Houqiang Li

In this way, CTDS balances the full utilization of global observation during training and the feasibility of decentralized execution for online inference.

Multi-agent Reinforcement Learning reinforcement-learning +2

MSDN: Mutually Semantic Distillation Network for Zero-Shot Learning

1 code implementation7 Mar 2022 Shiming Chen, Ziming Hong, Guo-Sen Xie, Wenhan Yang, Qinmu Peng, Kai Wang, Jian Zhao, Xinge You

Prior works either simply align the global features of an image with its associated class semantic vector or utilize unidirectional attention to learn the limited latent semantic representations, which could not effectively discover the intrinsic semantic knowledge e. g., attribute semantics) between visual and attribute features.

Transfer Learning Zero-Shot Learning

Revisiting QMIX: Discriminative Credit Assignment by Gradient Entropy Regularization

no code implementations9 Feb 2022 Jian Zhao, Yue Zhang, Xunhan Hu, Weixun Wang, Wengang Zhou, Jianye Hao, Jiangcheng Zhu, Houqiang Li

In cooperative multi-agent systems, agents jointly take actions and receive a team reward instead of individual rewards.

TransZero++: Cross Attribute-Guided Transformer for Zero-Shot Learning

1 code implementation16 Dec 2021 Shiming Chen, Ziming Hong, Guo-Sen Xie, Jian Zhao, Hao Li, Xinge You, Shuicheng Yan, Ling Shao

Analogously, VAT uses the similar feature augmentation encoder to refine the visual features, which are further applied in visual$\rightarrow$attribute decoder to learn visual-based attribute features.

Zero-Shot Learning

EDAssistant: Supporting Exploratory Data Analysis in Computational Notebooks with In-Situ Code Search and Recommendation

no code implementations15 Dec 2021 Xingjun Li, Yizhi Zhang, Justin Leung, Chengnian Sun, Jian Zhao

This paper presents EDAssistant, a JupyterLab extension that supports EDA with in-situ search of example notebooks and recommendation of useful APIs, powered by novel interactive visualization of search results.

Code Search

Multi-scale fusion self attention mechanism

no code implementations29 Sep 2021 Qibin Li, Nianmin Yao, Jian Zhao, Yanan Zhang

Based on the traditional attention mechanism, multi-scale fusion self attention extracts phrase information at different scales by setting convolution kernels at different levels, and calculates the corresponding attention matrix at different scales, so that the model can better extract phrase level information.

Relation Extraction

User-Centric Semi-Automated Infographics Authoring and Recommendation

no code implementations26 Aug 2021 Anjul Tyagi, Jian Zhao, Pushkar Patel, Swasti Khurana, Klaus Mueller

Based on the framework, we also propose an interactive tool, \name{}, for assisting novice designers with creating high-quality infographics from an input in a markdown format by offering recommendations of different design components of infographics.

The 2nd Anti-UAV Workshop & Challenge: Methods and Results

no code implementations23 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.

Object Tracking

Face.evoLVe: A High-Performance Face Recognition Library

1 code implementation19 Jul 2021 Qingzhong Wang, Pengfei Zhang, Haoyi Xiong, Jian Zhao

In this paper, we develop face. evoLVe -- a comprehensive library that collects and implements a wide range of popular deep learning-based methods for face recognition.

Face Alignment Face Recognition

Rethinking Sampling Strategies for Unsupervised Person Re-identification

2 code implementations7 Jul 2021 Xumeng Han, Xuehui Yu, Guorong Li, Jian Zhao, Gang Pan, Qixiang Ye, Jianbin Jiao, Zhenjun Han

Inspired by that, a simple yet effective approach is proposed, known as group sampling, which gathers groups of samples from the same class into a mini-batch.

Representation Learning Unsupervised Person Re-Identification

Interactive Dimensionality Reduction for Comparative Analysis

1 code implementation29 Jun 2021 Takanori Fujiwara, Xinhai Wei, Jian Zhao, Kwan-Liu Ma

However, existing DR methods provide limited capability and flexibility for such comparative analysis as each method is designed only for a narrow analysis target, such as identifying factors that most differentiate groups.

Contrastive Learning Dimensionality Reduction

SASICM A Multi-Task Benchmark For Subtext Recognition

no code implementations13 Jun 2021 Hua Yan, Feng Han, Junyi An, Weikang Xiao, Jian Zhao, Furao Shen

The F1 score of SASICMBERT, whose pretrained model is BERT, is 65. 12%, which is 0. 75% higher than that of SASICMg.

Image-to-Video Generation via 3D Facial Dynamics

no code implementations31 May 2021 Xiaoguang Tu, Yingtian Zou, Jian Zhao, Wenjie Ai, Jian Dong, Yuan YAO, Zhikang Wang, Guodong Guo, Zhifeng Li, Wei Liu, Jiashi Feng

Video generation from a single face image is an interesting problem and usually tackled by utilizing Generative Adversarial Networks (GANs) to integrate information from the input face image and a sequence of sparse facial landmarks.

Video Generation Video Prediction

Joint Face Image Restoration and Frontalization for Recognition

no code implementations12 May 2021 Xiaoguang Tu, Jian Zhao, Qiankun Liu, Wenjie Ai, Guodong Guo, Zhifeng Li, Wei Liu, Jiashi Feng

First, MDFR is a well-designed encoder-decoder architecture which extracts feature representation from an input face image with arbitrary low-quality factors and restores it to a high-quality counterpart.

Face Recognition Image Restoration

Faster and Simpler Siamese Network for Single Object Tracking

no code implementations7 May 2021 Shaokui Jiang, Baile Xu, Jian Zhao, Furao Shen

With the development of the deep network and the release for a series of large scale datasets for single object tracking, siamese networks have been proposed and perform better than most of the traditional methods.

Object Detection Object Tracking

IC Networks: Remodeling the Basic Unit for Convolutional Neural Networks

no code implementations6 Feb 2021 Junyi An, Fengshan Liu, Jian Zhao, Furao Shen

Inspired by the elastic collision model in physics, we present a general structure which can be integrated into the existing CNNs to improve their performance.

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.

IC Neuron: An Efficient Unit to Construct Neural Networks

no code implementations23 Nov 2020 Junyi An, Fengshan Liu, Jian Zhao, Furao Shen

We believe that the IC neuron can be a basic unit to build network structures.

Effective Fusion Factor in FPN for Tiny Object Detection

no code implementations4 Nov 2020 Yuqi Gong, Xuehui Yu, Yao Ding, Xiaoke Peng, Jian Zhao, Zhenjun Han

We propose a novel concept, fusion factor, to control information that deep layers deliver to shallow layers, for adapting FPN to tiny object detection.

Object Detection

OLALA: Object-Level Active Learning for Efficient Document Layout Annotation

1 code implementation5 Oct 2020 Zejiang Shen, Jian Zhao, Melissa Dell, YaoLiang Yu, Weining Li

Document images often have intricate layout structures, with numerous content regions (e. g. texts, figures, tables) densely arranged on each page.

Active Learning Object Detection

The 1st Tiny Object Detection Challenge:Methods and Results

1 code implementation16 Sep 2020 Xuehui Yu, Zhenjun Han, Yuqi Gong, Nan Jiang, Jian Zhao, Qixiang Ye, Jie Chen, Yuan Feng, Bin Zhang, Xiaodi Wang, Ying Xin, Jingwei Liu, Mingyuan Mao, Sheng Xu, Baochang Zhang, Shumin Han, Cheng Gao, Wei Tang, Lizuo Jin, Mingbo Hong, Yuchao Yang, Shuiwang Li, Huan Luo, Qijun Zhao, Humphrey Shi

The 1st Tiny Object Detection (TOD) Challenge aims to encourage research in developing novel and accurate methods for tiny object detection in images which have wide views, with a current focus on tiny person detection.

Human Detection Object Detection

A Visual Analytics Framework for Contrastive Network Analysis

no code implementations1 Aug 2020 Takanori Fujiwara, Jian Zhao, Francine Chen, Kwan-Liu Ma

A common network analysis task is comparison of two networks to identify unique characteristics in one network with respect to the other.

Contrastive Learning Representation Learning

Network Comparison with Interpretable Contrastive Network Representation Learning

2 code implementations25 May 2020 Takanori Fujiwara, Jian Zhao, Francine Chen, Yao-Liang Yu, Kwan-Liu Ma

This analysis task could be greatly assisted by contrastive learning, which is an emerging analysis approach to discover salient patterns in one dataset relative to another.

Contrastive Learning Representation Learning

Learning to Detect Head Movement in Unconstrained Remote Gaze Estimation in the Wild

no code implementations7 Apr 2020 Zhecan Wang, Jian Zhao, Cheng Lu, Han Huang, Fan Yang, Lianji Li, Yandong Guo

To better demonstrate the advantage of our methods, we further propose a new benchmark dataset with the most rich distribution of head-gaze combination reflecting real-world scenarios.

Gaze Estimation

Temporal Convolutional Attention-based Network For Sequence Modeling

1 code implementation28 Feb 2020 Hongyan Hao, Yan Wang, Yudi Xia, Jian Zhao, Furao Shen

So we propose an exploratory architecture referred to Temporal Convolutional Attention-based Network (TCAN) which combines temporal convolutional network and attention mechanism.

Pairwise Interactive Graph Attention Network for Context-Aware Recommendation

no code implementations18 Nov 2019 Yahui Liu, Furao Shen, Jian Zhao

PIGAT introduces the attention mechanism to consider the importance of each interacted user/item to both the user and the item, which captures user interests, item attractions and their influence on the recommendation context.

Graph Attention Recommendation Systems

SANVis: Visual Analytics for Understanding Self-Attention Networks

no code implementations13 Sep 2019 Cheonbok Park, Inyoup Na, Yongjang Jo, Sungbok Shin, Jaehyo Yoo, Bum Chul Kwon, Jian Zhao, Hyungjong Noh, Yeonsoo Lee, Jaegul Choo

Attention networks, a deep neural network architecture inspired by humans' attention mechanism, have seen significant success in image captioning, machine translation, and many other applications.

Image Captioning Machine Translation +1

Super Interaction Neural Network

1 code implementation29 May 2019 Yang Yao, Xu Zhang, Baile Xu, Furao Shen, Jian Zhao

Recent studies have demonstrated that the convolutional networks heavily rely on the quality and quantity of generated features.

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

Label Mapping Neural Networks with Response Consolidation for Class Incremental Learning

no code implementations20 May 2019 Xu Zhang, Yang Yao, Baile Xu, Lekun Mao, Furao Shen, Jian Zhao, QIngwei Lin

In this paper, it is the first time to discuss the difficulty without support of old classes in class incremental learning, which is called as softmax suppression problem.

class-incremental learning Incremental Learning +1

"Tom" pet robot applied to urban autism

no code implementations14 May 2019 Xingqian Li, Chenwei Lou, Jian Zhao, HuaPeng Wei, Hongwei Zhao

The consequent urban autism problem has become more and more serious.

Operation-aware Neural Networks for User Response Prediction

1 code implementation2 Apr 2019 Yi Yang, Baile Xu, Furao Shen, Jian Zhao

Many deep models are proposed to automatically learn high-order feature interactions.

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

Learning Generalizable and Identity-Discriminative Representations for Face Anti-Spoofing

1 code implementation17 Jan 2019 Xiaoguang Tu, Jian Zhao, Mei Xie, Guodong Du, Hengsheng Zhang, Jianshu Li, Zheng Ma, Jiashi Feng

Face anti-spoofing (a. k. a presentation attack detection) has drawn growing attention due to the high-security demand in face authentication systems.

Domain Adaptation Face Anti-Spoofing +1

Dynamic Conditional Networks for Few-Shot Learning

no code implementations ECCV 2018 Fang Zhao, Jian Zhao, Shuicheng Yan, Jiashi Feng

This paper proposes a novel Dynamic Conditional Convolutional Network (DCCN) to handle conditional few-shot learning, i. e, only a few training samples are available for each condition.

Face Generation Few-Shot Learning +3

Object Relation Detection Based on One-shot Learning

no code implementations16 Jul 2018 Li Zhou, Jian Zhao, Jianshu Li, Li Yuan, Jiashi Feng

Detecting the relations among objects, such as "cat on sofa" and "person ride horse", is a crucial task in image understanding, and beneficial to bridging the semantic gap between images and natural language.

One-Shot Learning

Weakly Supervised Phrase Localization With Multi-Scale Anchored Transformer Network

no code implementations CVPR 2018 Fang Zhao, Jianshu Li, Jian Zhao, Jiashi Feng

In this paper, we propose a novel weakly supervised model, Multi-scale Anchored Transformer Network (MATN), to accurately localize free-form textual phrases with only image-level supervision.

Region Proposal

Understanding Humans in Crowded Scenes: Deep Nested Adversarial Learning and A New Benchmark for Multi-Human Parsing

2 code implementations10 Apr 2018 Jian Zhao, Jianshu Li, Yu Cheng, Li Zhou, Terence Sim, Shuicheng Yan, Jiashi Feng

Despite the noticeable progress in perceptual tasks like detection, instance segmentation and human parsing, computers still perform unsatisfactorily on visually understanding humans in crowded scenes, such as group behavior analysis, person re-identification and autonomous driving, etc.

Autonomous Driving Instance Segmentation +4

Integrated Face Analytics Networks through Cross-Dataset Hybrid Training

no code implementations16 Nov 2017 Jianshu Li, Shengtao Xiao, Fang Zhao, Jian Zhao, Jianan Li, Jiashi Feng, Shuicheng Yan, Terence Sim

Specifically, iFAN achieves an overall F-score of 91. 15% on the Helen dataset for face parsing, a normalized mean error of 5. 81% on the MTFL dataset for facial landmark localization and an accuracy of 45. 73% on the BNU dataset for emotion recognition with a single model.

Face Alignment Face Parsing +1

Multiple-Human Parsing in the Wild

2 code implementations19 May 2017 Jianshu Li, Jian Zhao, Yunchao Wei, Congyan Lang, Yidong Li, Terence Sim, Shuicheng Yan, Jiashi Feng

To address the multi-human parsing problem, we introduce a new multi-human parsing (MHP) dataset and a novel multi-human parsing model named MH-Parser.

Multi-Human Parsing

A Good Practice Towards Top Performance of Face Recognition: Transferred Deep Feature Fusion

1 code implementation3 Apr 2017 Lin Xiong, Jayashree Karlekar, Jian Zhao, Yi Cheng, Yan Xu, Jiashi Feng, Sugiri Pranata, ShengMei Shen

In this paper, we propose a unified learning framework named Transferred Deep Feature Fusion (TDFF) targeting at the new IARPA Janus Benchmark A (IJB-A) face recognition dataset released by NIST face challenge.

Face Recognition Transfer Learning

Robust LSTM-Autoencoders for Face De-Occlusion in the Wild

no code implementations27 Dec 2016 Fang Zhao, Jiashi Feng, Jian Zhao, Wenhan Yang, Shuicheng Yan

The first one, named multi-scale spatial LSTM encoder, reads facial patches of various scales sequentially to output a latent representation, and occlusion-robustness is achieved owing to the fact that the influence of occlusion is only upon some of the patches.

Face Recognition

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