Search Results for author: Xiao Liu

Found 115 papers, 46 papers with code

An Attention-driven Two-stage Clustering Method for Unsupervised Person Re-Identification

no code implementations ECCV 2020 Zilong Ji, Xiaolong Zou, Xiaohan Lin, Xiao Liu, Tiejun Huang, Si Wu

By iteratively learning with the two strategies, the attentive regions are gradually shifted from the background to the foreground and the features become more discriminative.

Unsupervised Person Re-Identification

P-Tuning v2: Prompt Tuning Can Be Comparable to Fine-tuning Universally Across Scales and Tasks

2 code implementations14 Oct 2021 Xiao Liu, Kaixuan Ji, Yicheng Fu, Zhengxiao Du, Zhilin Yang, Jie Tang

Prompt tuning, which only tunes continuous prompts with a frozen language model, substantially reduces per-task storage and memory usage at training.

Language Modelling

LOF: Structure-Aware Line Tracking based on Optical Flow

no code implementations17 Sep 2021 Meixiang Quan, Zheng Chai, Xiao Liu

Lines provide the significantly richer geometric structural information about the environment than points, so lines are widely used in recent Visual Odometry (VO) works.

Line Detection Optical Flow Estimation +1

A Tutorial on Learning Disentangled Representations in the Imaging Domain

1 code implementation26 Aug 2021 Xiao Liu, Pedro Sanchez, Spyridon Thermos, Alison Q. O'Neil, Sotirios A. Tsaftaris

Disentangled representation learning has been proposed as an approach to learning general representations.

Representation Learning

Orthogonal Jacobian Regularization for Unsupervised Disentanglement in Image Generation

1 code implementation ICCV 2021 Yuxiang Wei, Yupeng Shi, Xiao Liu, Zhilong Ji, Yuan Gao, Zhongqin Wu, WangMeng Zuo

It simply encourages the variation of output caused by perturbations on different latent dimensions to be orthogonal, and the Jacobian with respect to the input is calculated to represent this variation.

Image Generation

Method Towards CVPR 2021 SimLocMatch Challenge

no code implementations10 Aug 2021 Xiaopeng Bi, Ran Yan, Zheng Chai, Haotian Zhang, Xiao Liu

This report describes Megvii-3D team's approach towards SimLocMatch Challenge @ CVPR 2021 Image Matching Workshop.

Method Towards CVPR 2021 Image Matching Challenge

no code implementations10 Aug 2021 Xiaopeng Bi, Yu Chen, Xinyang Liu, Dehao Zhang, Ran Yan, Zheng Chai, Haotian Zhang, Xiao Liu

This report describes Megvii-3D team's approach towards CVPR 2021 Image Matching Workshop.

SynCoBERT: Syntax-Guided Multi-Modal Contrastive Pre-Training for Code Representation

no code implementations10 Aug 2021 Xin Wang, Yasheng Wang, Fei Mi, Pingyi Zhou, Yao Wan, Xiao Liu, Li Li, Hao Wu, Jin Liu, Xin Jiang

Code representation learning, which aims to encode the semantics of source code into distributed vectors, plays an important role in recent deep-learning-based models for code intelligence.

Clone Detection Code Search +5

UniCon: Unified Context Network for Robust Active Speaker Detection

no code implementations5 Aug 2021 Yuanhang Zhang, Susan Liang, Shuang Yang, Xiao Liu, Zhongqin Wu, Shiguang Shan, Xilin Chen

Our solution is a novel, unified framework that focuses on jointly modeling multiple types of contextual information: spatial context to indicate the position and scale of each candidate's face, relational context to capture the visual relationships among the candidates and contrast audio-visual affinities with each other, and temporal context to aggregate long-term information and smooth out local uncertainties.

Audio-Visual Active Speaker Detection

Structured Multi-modal Feature Embedding and Alignment for Image-Sentence Retrieval

no code implementations5 Aug 2021 Xuri Ge, Fuhai Chen, Joemon M. Jose, Zhilong Ji, Zhongqin Wu, Xiao Liu

In this work, we propose to address the above issue from two aspects: (i) constructing intrinsic structure (along with relations) among the fragments of respective modalities, e. g., "dog $\to$ play $\to$ ball" in semantic structure for an image, and (ii) seeking explicit inter-modal structural and semantic correspondence between the visual and textual modalities.

Semantic correspondence

Rethinking Hard-Parameter Sharing in Multi-Domain Learning

no code implementations23 Jul 2021 Lijun Zhang, Qizheng Yang, Xiao Liu, Hui Guan

One common sharing practice is to share bottom layers of a deep neural network among domains while using separate top layers for each domain.

Fine-Grained Image Classification Multi-Task Learning

Locality-aware Channel-wise Dropout for Occluded Face Recognition

no code implementations20 Jul 2021 Mingjie He, Jie Zhang, Shiguang Shan, Xiao Liu, Zhongqin Wu, Xilin Chen

Furthermore, by randomly dropping out several feature channels, our method can well simulate the occlusion of larger area.

Face Recognition

Unsupervised Neural Rendering for Image Hazing

no code implementations14 Jul 2021 Boyun Li, Yijie Lin, Xiao Liu, Peng Hu, Jiancheng Lv, Xi Peng

To generate plausible haze, we study two less-touched but challenging problems in hazy image rendering, namely, i) how to estimate the transmission map from a single image without auxiliary information, and ii) how to adaptively learn the airlight from exemplars, i. e., unpaired real hazy images.

Image Dehazing Neural Rendering

Controllable cardiac synthesis via disentangled anatomy arithmetic

1 code implementation4 Jul 2021 Spyridon Thermos, Xiao Liu, Alison O'Neil, Sotirios A. Tsaftaris

Motivated by the ability to disentangle images into spatial anatomy (tensor) factors and accompanying imaging (vector) representations, we propose a framework termed "disentangled anatomy arithmetic", in which a generative model learns to combine anatomical factors of different input images such that when they are re-entangled with the desired imaging modality (e. g. MRI), plausible new cardiac images are created with the target characteristics.

Boost-R: Gradient Boosted Trees for Recurrence Data

no code implementations3 Jul 2021 Xiao Liu, Rong pan

Boost-R constructs an ensemble of gradient boosted additive trees to estimate the cumulative intensity function of the recurrent event process, where a new tree is added to the ensemble by minimizing the regularized L2 distance between the observed and predicted cumulative intensity.

1st Place Solutions for UG2+ Challenge 2021 -- (Semi-)supervised Face detection in the low light condition

no code implementations2 Jul 2021 Pengcheng Wang, Lingqiao Ji, Zhilong Ji, Yuan Gao, Xiao Liu

In this technical report, we briefly introduce the solution of our team "TAL-ai" for (Semi-) supervised Face detection in the low light condition in UG2+ Challenge in CVPR 2021.

Face Detection Image Enhancement +1

Multi-Granularity Network with Modal Attention for Dense Affective Understanding

no code implementations18 Jun 2021 Baoming Yan, Lin Wang, Ke Gao, Bo Gao, Xiao Liu, Chao Ban, Jiang Yang, Xiaobo Li

Video affective understanding, which aims to predict the evoked expressions by the video content, is desired for video creation and recommendation.

A Self-supervised Method for Entity Alignment

1 code implementation17 Jun 2021 Xiao Liu, Haoyun Hong, Xinghao Wang, Zeyi Chen, Evgeny Kharlamov, Yuxiao Dong, Jie Tang

We present SelfKG by leveraging this discovery to design a contrastive learning strategy across two KGs.

Contrastive Learning Entity Alignment +2

3rd Place Solution for Short-video Face Parsing Challenge

no code implementations14 Jun 2021 Xiao Liu, XiaoFei Si, Jiangtao Xie

Benefiting from the edge information and edge attention loss, the proposed EANet achieves 86. 16\% accuracy in the Short-video Face Parsing track of the 3rd Person in Context (PIC) Workshop and Challenge, ranked the third place.

Face Parsing

Image Inpainting by End-to-End Cascaded Refinement with Mask Awareness

1 code implementation28 Apr 2021 Manyu Zhu, Dongliang He, Xin Li, Chao Li, Fu Li, Xiao Liu, Errui Ding, Zhaoxiang Zhang

Inpainting arbitrary missing regions is challenging because learning valid features for various masked regions is nontrivial.

Image Inpainting

All NLP Tasks Are Generation Tasks: A General Pretraining Framework

1 code implementation18 Mar 2021 Zhengxiao Du, Yujie Qian, Xiao Liu, Ming Ding, Jiezhong Qiu, Zhilin Yang, Jie Tang

On the other hand, NLP tasks are different in nature, with three main categories being classification, unconditional generation, and conditional generation.

Abstractive Text Summarization Classification +4

GPT Understands, Too

4 code implementations18 Mar 2021 Xiao Liu, Yanan Zheng, Zhengxiao Du, Ming Ding, Yujie Qian, Zhilin Yang, Jie Tang

On the SuperGlue benchmark, GPTs achieve comparable and sometimes better performance to similar-sized BERTs in supervised learning.

LAMA Natural Language Understanding

Pseudo-ISP: Learning Pseudo In-camera Signal Processing Pipeline from A Color Image Denoiser

1 code implementation18 Mar 2021 Yue Cao, Xiaohe Wu, Shuran Qi, Xiao Liu, Zhongqin Wu, WangMeng Zuo

To begin with, the pre-trained denoiser is used to generate the pseudo clean images for the test images.


Understanding WeChat User Preferences and "Wow" Diffusion

1 code implementation4 Mar 2021 Fanjin Zhang, Jie Tang, Xueyi Liu, Zhenyu Hou, Yuxiao Dong, Jing Zhang, Xiao Liu, Ruobing Xie, Kai Zhuang, Xu Zhang, Leyu Lin, Philip S. Yu

"Top Stories" is a novel friend-enhanced recommendation engine in WeChat, in which users can read articles based on preferences of both their own and their friends.

Graph Representation Learning Social and Information Networks

A Novel Graph-based Computation Offloading Strategy for Workflow Applications in Mobile Edge Computing

no code implementations24 Feb 2021 Xuejun Li, Tianxiang Chen, Dong Yuan, Jia Xu, Xiao Liu

To achieve better Quality of Service (QoS), for instance, faster response time and lower energy consumption, computation offloading is widely used in the MEC environment.

Edge-computing Distributed, Parallel, and Cluster Computing C.2.4

Artificial Intelligence Enhanced Rapid and Efficient Diagnosis of Mycoplasma Pneumoniae Pneumonia in Children Patients

1 code implementation20 Feb 2021 Chenglin Pan, Kuan Yan, Xiao Liu, Yanjie Chen, Yanyan Luo, Xiaoming Li, Zhenguo Nie, Xinjun Liu

Artificial intelligence methods have been increasingly turning into a potentially powerful tool in the diagnosis and management of diseases.

Feature Importance

GraphGallery: A Platform for Fast Benchmarking and Easy Development of Graph Neural Networks Based Intelligent Software

1 code implementation16 Feb 2021 Jintang Li, Kun Xu, Liang Chen, Zibin Zheng, Xiao Liu

Graph Neural Networks (GNNs) have recently shown to be powerful tools for representing and analyzing graph data.

Improved Signed Distance Function for 2D Real-time SLAM and Accurate Localization

no code implementations20 Jan 2021 Xingyin Fu, Zheng Fang, Xizhen Xiao, Yijia He, Xiao Liu

In this paper, we propose an improved Signed Distance Function (SDF) for both 2D SLAM and pure localization to improve the accuracy of mapping and localization.

Pose Estimation

Integrated 3C in NOMA-enabled Remote-E-Health Systems

no code implementations5 Jan 2021 Xiao Liu, Yuanwei Liu, Zhong Yang, Xinwei Yue, Chuan Wang, Yue Chen

A novel framework is proposed to integrate communication, control and computing (3C) into the fifth-generation and beyond (5GB) wireless networks for satisfying the ultra-reliable low-latency connectivity requirements of remote-e-Health systems.

News-Driven Stock Prediction Using Noisy Equity State Representation

no code implementations1 Jan 2021 Xiao Liu, Heyan Huang, Yue Zhang

News-driven stock prediction investigates the correlation between news events and stock price movements.

Stock Prediction

Understanding Health Video Engagement: An Interpretable Deep Learning Approach

no code implementations21 Dec 2020 Jiaheng Xie, Yidong Chai, Xiao Liu

Understanding how health misinformation is transmitted is an urgent goal for researchers, social media platforms, health sectors, and policymakers to mitigate those ramifications.

Misinformation Video Description

SID-NISM: A Self-supervised Low-light Image Enhancement Framework

no code implementations16 Dec 2020 Lijun Zhang, Xiao Liu, Erik Learned-Miller, Hui Guan

When capturing images in low-light conditions, the images often suffer from low visibility, which not only degrades the visual aesthetics of images, but also significantly degenerates the performance of many computer vision algorithms.

Low-Light Image Enhancement

Robotic Communications for 5G and Beyond: Challenges and Research Opportunities

no code implementations9 Dec 2020 Yuanwei Liu, Xiao Liu, Xinyu Gao, Xidong Mu, Xiangwei Zhou, Octavia A. Dobre, H. Vincent Poor

Furthermore, dynamic trajectory design and resource allocation for both indoor and outdoor robots are provided to verify the performance of robotic communications in the context of typical robotic application scenarios.

Robotics Systems and Control Signal Processing Systems and Control

Intelligent Reflecting Surface Aided Multi-Cell NOMA Networks

no code implementations7 Dec 2020 Wanli Ni, Xiao Liu, Yuanwei Liu, Hui Tian, Yue Chen

This paper proposes a novel framework of resource allocation in intelligent reflecting surface (IRS) aided multi-cell non-orthogonal multiple access (NOMA) networks, where a sum-rate maximization problem is formulated.

Path Design and Resource Management for NOMA enhanced Indoor Intelligent Robots

no code implementations23 Nov 2020 Ruikang Zhong, Xiao Liu, Yuanwei Liu, Yue Chen, Xianbin Wang

Our simulation results demonstrate that 1) With the aid of NOMA techniques, the communication reliability of IRs is effectively improved; 2) The radio map is qualified to be a virtual training environment, and its statistical channel state information improves training efficiency by about 30%; 3) The proposed DT-DPG algorithm is superior to the conventional deep deterministic policy gradient (DDPG) algorithm in terms of optimization performance, training time, and anti-local optimum ability.

Language Models are Open Knowledge Graphs

2 code implementations22 Oct 2020 Chenguang Wang, Xiao Liu, Dawn Song

This paper shows how to construct knowledge graphs (KGs) from pre-trained language models (e. g., BERT, GPT-2/3), without human supervision.

Knowledge Graphs

Multi-Agent Reinforcement Learning in NOMA-aided UAV Networks for Cellular Offloading

1 code implementation18 Oct 2020 Ruikang Zhong, Xiao Liu, Yuanwei Liu, Yue Chen

Afterward, a mutual deep Q-network (MDQN) algorithm is proposed to jointly determine the optimal 3D trajectory and power allocation of UAVs.

Multi-agent Reinforcement Learning

NOMA in UAV-aided cellular offloading: A machine learning approach

no code implementations18 Oct 2020 Ruikang Zhong, Xiao Liu, Yuanwei Liu, Yue Chen

A novel framework is proposed for cellular offloading with the aid of multiple unmanned aerial vehicles (UAVs), while non-orthogonal multiple access (NOMA) technique is employed at each UAV to further improve the spectrum efficiency of the wireless network.

Difference-in-Differences: Bridging Normalization and Disentanglement in PG-GAN

no code implementations16 Oct 2020 Xiao Liu, Jiajie Zhang, Siting Li, Zuotong Wu, Yang Yu

We discover that pixel normalization causes object entanglement by in-painting the area occupied by ablated objects.

Machine Learning Empowered Trajectory and Passive Beamforming Design in UAV-RIS Wireless Networks

no code implementations6 Oct 2020 Xiao Liu, Yuanwei Liu, Yue Chen

The energy consumption minimizing problem is formulated by jointly designing the movement of the UAV, phase shifts of the RIS, power allocation policy from the UAV to MUs, as well as determining the dynamic decoding order.


TP-LSD: Tri-Points Based Line Segment Detector

1 code implementation ECCV 2020 Siyu Huang, Fangbo Qin, Pengfei Xiong, Ning Ding, Yijia He, Xiao Liu

To realize one-step detection with a faster and more compact model, we introduce the tri-points representation, converting the line segment detection to the end-to-end prediction of a root-point and two endpoints for each line segment.

Line Segment Detection

Measuring the Biases and Effectiveness of Content-Style Disentanglement

1 code implementation27 Aug 2020 Xiao Liu, Spyridon Thermos, Gabriele Valvano, Agisilaos Chartsias, Alison O'Neil, Sotirios A. Tsaftaris

In this paper, we conduct an empirical study to investigate the role of different biases in content-style disentanglement settings and unveil the relationship between the degree of disentanglement and task performance.

Image-to-Image Translation

Disentangled Representations for Domain-generalized Cardiac Segmentation

1 code implementation26 Aug 2020 Xiao Liu, Spyridon Thermos, Agisilaos Chartsias, Alison O'Neil, Sotirios A. Tsaftaris

Robust cardiac image segmentation is still an open challenge due to the inability of the existing methods to achieve satisfactory performance on unseen data of different domains.

Cardiac Segmentation Data Augmentation +2

Dialogue State Induction Using Neural Latent Variable Models

1 code implementation13 Aug 2020 Qingkai Min, Libo Qin, Zhiyang Teng, Xiao Liu, Yue Zhang

Dialogue state modules are a useful component in a task-oriented dialogue system.

Latent Variable Models

Reconfigurable Intelligent Surfaces: Principles and Opportunities

no code implementations7 Jul 2020 Yuanwei Liu, Xiao Liu, Xidong Mu, Tianwei Hou, Jiaqi Xu, Marco Di Renzo, Naofal Al-Dhahir

In this context, we provide a comprehensive overview of the state-of-the-art on RISs, with focus on their operating principles, performance evaluation, beamforming design and resource management, applications of machine learning to RIS-enhanced wireless networks, as well as the integration of RISs with other emerging technologies.

Resource Allocation for Multi-Cell IRS-Aided NOMA Networks

no code implementations21 Jun 2020 Wanli Ni, Xiao Liu, Yuanwei Liu, Hui Tian, Yue Chen

This paper proposes a novel framework of resource allocation in multi-cell intelligent reflecting surface (IRS) aided non-orthogonal multiple access (NOMA) networks, where an IRS is deployed to enhance the wireless service.

Self-supervised Learning: Generative or Contrastive

1 code implementation15 Jun 2020 Xiao Liu, Fanjin Zhang, Zhenyu Hou, Zhaoyu Wang, Li Mian, Jing Zhang, Jie Tang

As an alternative, self-supervised learning attracts many researchers for its soaring performance on representation learning in the last several years.

Graph Learning Representation Learning +1

Online Non-convex Learning for River Pollution Source Identification

no code implementations22 May 2020 Wenjie Huang, Jing Jiang, Xiao Liu

In this paper, novel gradient based online learning algorithms are developed to investigate an important environmental application: real-time river pollution source identification, which aims at estimating the released mass, the location and the released time of a river pollution source based on downstream sensor data monitoring the pollution concentration.

Studying Product Competition Using Representation Learning

no code implementations21 May 2020 Fanglin Chen, Xiao Liu, Davide Proserpio, Isamar Troncoso, Feiyu Xiong

We show that, compared with state-of-the-art models, our approach is faster, and can produce more accurate demand forecasts and price elasticities.

Causal Inference Decision Making +1

Neighborhood Matching Network for Entity Alignment

1 code implementation ACL 2020 Yuting Wu, Xiao Liu, Yansong Feng, Zheng Wang, Dongyan Zhao

This paper presents Neighborhood Matching Network (NMN), a novel entity alignment framework for tackling the structural heterogeneity challenge.

Entity Alignment Graph Sampling +1

Using Noisy Self-Reports to Predict Twitter User Demographics

1 code implementation1 May 2020 Zach Wood-Doughty, Paiheng Xu, Xiao Liu, Mark Dredze

We present a method to identify self-reports of race and ethnicity from Twitter profile descriptions.

M^3VSNet: Unsupervised Multi-metric Multi-view Stereo Network

1 code implementation30 Apr 2020 Baichuan Huang, Hongwei Yi, Can Huang, Yijia He, Jingbin Liu, Xiao Liu

To improve the robustness and completeness of point cloud reconstruction, we propose a novel multi-metric loss function that combines pixel-wise and feature-wise loss function to learn the inherent constraints from different perspectives of matching correspondences.

M^3VSNet: Unsupervised Multi-metric Multi-view Stereo Network

2 code implementations21 Apr 2020 Baichuan Huang, Hongwei Yi, Can Huang, Yijia He, Jingbin Liu, Xiao Liu

To improve the robustness and completeness of point cloud reconstruction, we propose a novel multi-metric loss function that combines pixel-wise and feature-wise loss function to learn the inherent constraints from different perspectives of matching correspondences.

Have you forgotten? A method to assess if machine learning models have forgotten data

no code implementations21 Apr 2020 Xiao Liu, Sotirios A. Tsaftaris

In the era of deep learning, aggregation of data from several sources is a common approach to ensuring data diversity.

Leveraging Planar Regularities for Point Line Visual-Inertial Odometry

no code implementations16 Apr 2020 Xin Li, Yijia He, Jinlong Lin, Xiao Liu

To improve the accuracy of 3D mesh generation and localization, we propose a tightly-coupled monocular VIO system, PLP-VIO, which exploits point features and line features as well as plane regularities.

Predictions of 2019-nCoV Transmission Ending via Comprehensive Methods

no code implementations12 Feb 2020 Tianyu Zeng, Yunong Zhang, Zhenyu Li, Xiao Liu, Binbin Qiu

Since the SARS outbreak in 2003, a lot of predictive epidemiological models have been proposed.

RIS Enhanced Massive Non-orthogonal Multiple Access Networks: Deployment and Passive Beamforming Design

no code implementations28 Jan 2020 Xiao Liu, Yuanwei Liu, Yue Chen, H. Vincent Poor

A novel framework is proposed for the deployment and passive beamforming design of a reconfigurable intelligent surface (RIS) with the aid of non-orthogonal multiple access (NOMA) technology.

Artificial Intelligence Aided Next-Generation Networks Relying on UAVs

no code implementations28 Jan 2020 Xiao Liu, Mingzhe Chen, Yuanwei Liu, Yue Chen, Shuguang Cui, Lajos Hanzo

Artificial intelligence (AI) assisted unmanned aerial vehicle (UAV) aided next-generation networking is proposed for dynamic environments.

Push-pull Feedback Implements Hierarchical Information Retrieval Efficiently

1 code implementation NeurIPS 2019 Xiao Liu, Xiaolong Zou, Zilong Ji, Gengshuo Tian, Yuanyuan Mi, Tiejun Huang, K. Y. Michael Wong, Si Wu

Experimental data has revealed that in addition to feedforward connections, there exist abundant feedback connections in a neural pathway.

Information Retrieval

Dynamic Instance Normalization for Arbitrary Style Transfer

no code implementations16 Nov 2019 Yongcheng Jing, Xiao Liu, Yukang Ding, Xinchao Wang, Errui Ding, Mingli Song, Shilei Wen

Prior normalization methods rely on affine transformations to produce arbitrary image style transfers, of which the parameters are computed in a pre-defined way.

Style Transfer

TruNet: Short Videos Generation from Long Videos via Story-Preserving Truncation

no code implementations14 Oct 2019 Fan Yang, Xiao Liu, Dongliang He, Chuang Gan, Jian Wang, Chao Li, Fu Li, Shilei Wen

In this work, we introduce a new problem, named as {\em story-preserving long video truncation}, that requires an algorithm to automatically truncate a long-duration video into multiple short and attractive sub-videos with each one containing an unbroken story.

Video Summarization

Jointly Learning Entity and Relation Representations for Entity Alignment

1 code implementation IJCNLP 2019 Yuting Wu, Xiao Liu, Yansong Feng, Zheng Wang, Dongyan Zhao

Entity alignment is a viable means for integrating heterogeneous knowledge among different knowledge graphs (KGs).

Ranked #10 on Entity Alignment on DBP15k zh-en (using extra training data)

Entity Alignment Entity Embeddings +1

Image Inpainting with Learnable Bidirectional Attention Maps

1 code implementation ICCV 2019 Chaohao Xie, Shaohui Liu, Chao Li, Ming-Ming Cheng, WangMeng Zuo, Xiao Liu, Shilei Wen, Errui Ding

Most convolutional network (CNN)-based inpainting methods adopt standard convolution to indistinguishably treat valid pixels and holes, making them limited in handling irregular holes and more likely to generate inpainting results with color discrepancy and blurriness.

Image Inpainting

Deep Concept-wise Temporal Convolutional Networks for Action Localization

2 code implementations26 Aug 2019 Xin Li, Tianwei Lin, Xiao Liu, Chuang Gan, WangMeng Zuo, Chao Li, Xiang Long, Dongliang He, Fu Li, Shilei Wen

In this paper, we empirically find that stacking more conventional temporal convolution layers actually deteriorates action classification performance, possibly ascribing to that all channels of 1D feature map, which generally are highly abstract and can be regarded as latent concepts, are excessively recombined in temporal convolution.

Action Classification Action Localization

Relation-Aware Entity Alignment for Heterogeneous Knowledge Graphs

1 code implementation22 Aug 2019 Yuting Wu, Xiao Liu, Yansong Feng, Zheng Wang, Rui Yan, Dongyan Zhao

Entity alignment is the task of linking entities with the same real-world identity from different knowledge graphs (KGs), which has been recently dominated by embedding-based methods.

Ranked #12 on Entity Alignment on DBP15k zh-en (using extra training data)

Entity Alignment Entity Embeddings +1

BMN: Boundary-Matching Network for Temporal Action Proposal Generation

9 code implementations ICCV 2019 Tianwei Lin, Xiao Liu, Xin Li, Errui Ding, Shilei Wen

To address these difficulties, we introduce the Boundary-Matching (BM) mechanism to evaluate confidence scores of densely distributed proposals, which denote a proposal as a matching pair of starting and ending boundaries and combine all densely distributed BM pairs into the BM confidence map.

Action Detection Action Recognition +1

Open Domain Event Extraction Using Neural Latent Variable Models

1 code implementation ACL 2019 Xiao Liu, He-Yan Huang, Yue Zhang

We consider open domain event extraction, the task of extracting unconstraint types of events from news clusters.

Event Extraction Latent Variable Models

A Soft Label Strategy for Target-Level Sentiment Classification

no code implementations WS 2019 Da Yin, Xiao Liu, Xiuyu Wu, Baobao Chang

In this paper, we propose a soft label approach to target-level sentiment classification task, in which a history-based soft labeling model is proposed to measure the possibility of a context word as an opinion word.

Classification General Classification +1

Adapting Image Super-Resolution State-of-the-arts and Learning Multi-model Ensemble for Video Super-Resolution

no code implementations7 May 2019 Chao Li, Dongliang He, Xiao Liu, Yukang Ding, Shilei Wen

Recently, image super-resolution has been widely studied and achieved significant progress by leveraging the power of deep convolutional neural networks.

Image Super-Resolution Video Super-Resolution

STGAN: A Unified Selective Transfer Network for Arbitrary Image Attribute Editing

2 code implementations CVPR 2019 Ming Liu, Yukang Ding, Min Xia, Xiao Liu, Errui Ding, WangMeng Zuo, Shilei Wen

Arbitrary attribute editing generally can be tackled by incorporating encoder-decoder and generative adversarial networks.


DF-SLAM: A Deep-Learning Enhanced Visual SLAM System based on Deep Local Features

no code implementations22 Jan 2019 Rong Kang, Jieqi Shi, Xueming Li, Yang Liu, Xiao Liu

As the foundation of driverless vehicle and intelligent robots, Simultaneous Localization and Mapping(SLAM) has attracted much attention these days.

Simultaneous Localization and Mapping

Read, Watch, and Move: Reinforcement Learning for Temporally Grounding Natural Language Descriptions in Videos

1 code implementation21 Jan 2019 Dongliang He, Xiang Zhao, Jizhou Huang, Fu Li, Xiao Liu, Shilei Wen

The task of video grounding, which temporally localizes a natural language description in a video, plays an important role in understanding videos.

Decision Making Multi-Task Learning

Distant Supervision for Relation Extraction with Linear Attenuation Simulation and Non-IID Relevance Embedding

no code implementations22 Dec 2018 Changsen Yuan, He-Yan Huang, Chong Feng, Xiao Liu, Xiaochi Wei

Distant supervision for relation extraction is an efficient method to reduce labor costs and has been widely used to seek novel relational facts in large corpora, which can be identified as a multi-instance multi-label problem.

Relation Extraction

StNet: Local and Global Spatial-Temporal Modeling for Action Recognition

3 code implementations5 Nov 2018 Dongliang He, Zhichao Zhou, Chuang Gan, Fu Li, Xiao Liu, Yandong Li, Li-Min Wang, Shilei Wen

In this paper, in contrast to the existing CNN+RNN or pure 3D convolution based approaches, we explore a novel spatial temporal network (StNet) architecture for both local and global spatial-temporal modeling in videos.

Action Recognition

Fine-grained Video Categorization with Redundancy Reduction Attention

no code implementations ECCV 2018 Chen Zhu, Xiao Tan, Feng Zhou, Xiao Liu, Kaiyu Yue, Errui Ding, Yi Ma

Specifically, it firstly summarizes the video by weight-summing all feature vectors in the feature maps of selected frames with a spatio-temporal soft attention, and then predicts which channels to suppress or to enhance according to this summary with a learned non-linear transform.

Video Classification

Improving Annotation for 3D Pose Dataset of Fine-Grained Object Categories

2 code implementations19 Oct 2018 Yaming Wang, Xiao Tan, Yi Yang, Ziyu Li, Xiao Liu, Feng Zhou, Larry S. Davis

Existing 3D pose datasets of object categories are limited to generic object types and lack of fine-grained information.

3D Pose Estimation Object Recognition

PANDA: AdaPtive Noisy Data Augmentation for Regularization of Undirected Graphical Models

no code implementations11 Oct 2018 Yi-Nan Li, Xiao Liu, Fang Liu

We propose an AdaPtive Noise Augmentation (PANDA) technique to regularize the estimation and construction of undirected graphical models.

Data Augmentation Variable Selection

Real-time Scholarly Retweeting Prediction System

no code implementations COLING 2018 Zhunchen Luo, Xiao Liu

At last, we combine scholarly features with the Tweet Scholar Blocks to predict whether a scholarly tweet will be retweeted.

CerfGAN: A Compact, Effective, Robust, and Fast Model for Unsupervised Multi-Domain Image-to-Image Translation

no code implementations28 May 2018 Xiao Liu, Shengchuan Zhang, Hong Liu, Xin Liu, Cheng Deng, Rongrong Ji

In principle, CerfGAN contains a novel component, i. e., a multi-class discriminator (MCD), which gives the model an extremely powerful ability to match multiple translation mappings.

Face Hallucination Image-to-Image Translation +2

Attention Clusters: Purely Attention Based Local Feature Integration for Video Classification

2 code implementations CVPR 2018 Xiang Long, Chuang Gan, Gerard de Melo, Jiajun Wu, Xiao Liu, Shilei Wen

In this paper, however, we show that temporal information, especially longer-term patterns, may not be necessary to achieve competitive results on common video classification datasets.

Classification General Classification +1

Revisiting the Effectiveness of Off-the-shelf Temporal Modeling Approaches for Large-scale Video Classification

no code implementations12 Aug 2017 Yunlong Bian, Chuang Gan, Xiao Liu, Fu Li, Xiang Long, Yandong Li, Heng Qi, Jie zhou, Shilei Wen, Yuanqing Lin

Experiment results on the challenging Kinetics dataset demonstrate that our proposed temporal modeling approaches can significantly improve existing approaches in the large-scale video recognition tasks.

Action Classification General Classification +2

Deep Metric Learning with Angular Loss

1 code implementation ICCV 2017 Jian Wang, Feng Zhou, Shilei Wen, Xiao Liu, Yuanqing Lin

The modern image search system requires semantic understanding of image, and a key yet under-addressed problem is to learn a good metric for measuring the similarity between images.

Image Retrieval Metric Learning

Temporal Modeling Approaches for Large-scale Youtube-8M Video Understanding

1 code implementation14 Jul 2017 Fu Li, Chuang Gan, Xiao Liu, Yunlong Bian, Xiang Long, Yandong Li, Zhichao Li, Jie zhou, Shilei Wen

This paper describes our solution for the video recognition task of the Google Cloud and YouTube-8M Video Understanding Challenge that ranked the 3rd place.

Video Recognition Video Understanding

Kernel Pooling for Convolutional Neural Networks

no code implementations CVPR 2017 Yin Cui, Feng Zhou, Jiang Wang, Xiao Liu, Yuanqing Lin, Serge Belongie

We demonstrate how to approximate kernels such as Gaussian RBF up to a given order using compact explicit feature maps in a parameter-free manner.

Face Recognition Fine-Grained Visual Categorization +2

Deep Speaker: an End-to-End Neural Speaker Embedding System

15 code implementations5 May 2017 Chao Li, Xiaokong Ma, Bing Jiang, Xiangang Li, Xuewei Zhang, Xiao Liu, Ying Cao, Ajay Kannan, Zhenyao Zhu

We present Deep Speaker, a neural speaker embedding system that maps utterances to a hypersphere where speaker similarity is measured by cosine similarity.

Speaker Identification Speaker Recognition

Dynamic Computational Time for Visual Attention

1 code implementation30 Mar 2017 Zhichao Li, Yi Yang, Xiao Liu, Feng Zhou, Shilei Wen, Wei Xu

We propose a dynamic computational time model to accelerate the average processing time for recurrent visual attention (RAM).

Localizing by Describing: Attribute-Guided Attention Localization for Fine-Grained Recognition

no code implementations20 May 2016 Xiao Liu, Jiang Wang, Shilei Wen, Errui Ding, Yuanqing Lin

By designing a novel reward strategy, we are able to learn to locate regions that are spatially and semantically distinctive with reinforcement learning algorithm.

Deep Embedding for Spatial Role Labeling

no code implementations28 Mar 2016 Oswaldo Ludwig, Xiao Liu, Parisa Kordjamshidi, Marie-Francine Moens

This paper introduces the visually informed embedding of word (VIEW), a continuous vector representation for a word extracted from a deep neural model trained using the Microsoft COCO data set to forecast the spatial arrangements between visual objects, given a textual description.

Fully Convolutional Attention Networks for Fine-Grained Recognition

no code implementations22 Mar 2016 Xiao Liu, Tian Xia, Jiang Wang, Yi Yang, Feng Zhou, Yuanqing Lin

Fine-grained recognition is challenging due to its subtle local inter-class differences versus large intra-class variations such as poses.

Learning Contextual Dependencies with Convolutional Hierarchical Recurrent Neural Networks

no code implementations13 Sep 2015 Zhen Zuo, Bing Shuai, Gang Wang, Xiao Liu, Xingxing Wang, Bing Wang

In this manuscript, we integrate CNNs with HRNNs, and develop end-to-end convolutional hierarchical recurrent neural networks (C-HRNNs).

General Classification Image Classification

A Robust Point Sets Matching Method

no code implementations4 Nov 2014 Xiao Liu, Congying Han, Tiande Guo

Point sets matching method is very important in computer vision, feature extraction, fingerprint matching, motion estimation and so on.

Motion Estimation

Semi-Supervised Coupled Dictionary Learning for Person Re-identification

no code implementations CVPR 2014 Xiao Liu, Mingli Song, DaCheng Tao, Xingchen Zhou, Chun Chen, Jiajun Bu

In this paper, to bridge the human appearance variations across cameras, two coupled dictionaries that relate to the gallery and probe cameras are jointly learned in the training phase from both labeled and unlabeled images.

Dictionary Learning Person Re-Identification

Semi-supervised Node Splitting for Random Forest Construction

no code implementations CVPR 2013 Xiao Liu, Mingli Song, DaCheng Tao, Zicheng Liu, Luming Zhang, Chun Chen, Jiajun Bu

Node splitting is an important issue in Random Forest but robust splitting requires a large number of training samples.

Semantic Segmentation

Probabilistic Graphlet Cut: Exploiting Spatial Structure Cue for Weakly Supervised Image Segmentation

no code implementations CVPR 2013 Luming Zhang, Mingli Song, Zicheng Liu, Xiao Liu, Jiajun Bu, Chun Chen

Finally, we propose a novel image segmentation algorithm, called graphlet cut, that leverages the learned graphlet distribution in measuring the homogeneity of a set of spatially structured superpixels.

Semantic Segmentation

Cannot find the paper you are looking for? You can Submit a new open access paper.