Search Results for author: Zheng Wang

Found 99 papers, 24 papers with code

Towards Generalizable Person Re-identification with a Bi-stream Generative Model

no code implementations19 Jun 2022 Xin Xu, Wei Liu, Zheng Wang, Ruiming Hu, Qi Tian

Guided by original pedestrian images, one stream is employed to learn a camera-invariant global feature for the CC problem via filtering cross-camera interference factors.

Domain Generalization Generalizable Person Re-identification

Improving Generalization of Metric Learning via Listwise Self-distillation

1 code implementation17 Jun 2022 Zelong Zeng, Fan Yang, Zheng Wang, Shin'ichi Satoh

Most deep metric learning (DML) methods employ a strategy that forces all positive samples to be close in the embedding space while keeping them away from negative ones.

Metric Learning

Unsupervised Foggy Scene Understanding via Self Spatial-Temporal Label Diffusion

1 code implementation10 Jun 2022 Liang Liao, WenYi Chen, Jing Xiao, Zheng Wang, Chia-Wen Lin, Shin'ichi Satoh

Specifically, based on the two discoveries of local spatial similarity and adjacent temporal correspondence of the sequential image data, we propose a novel Target-Domain driven pseudo label Diffusion (TDo-Dif) scheme.

Autonomous Driving Scene Understanding +3

Geo-Localization via Ground-to-Satellite Cross-View Image Retrieval

no code implementations22 May 2022 Zelong Zeng, Zheng Wang, Fan Yang, Shin'ichi Satoh

The large variation of viewpoint and irrelevant content around the target always hinder accurate image retrieval and its subsequent tasks.

Image Retrieval Representation Learning

Spatial-Temporal Space Hand-in-Hand: Spatial-Temporal Video Super-Resolution via Cycle-Projected Mutual Learning

no code implementations CVPR 2022 Mengshun Hu, Kui Jiang, Liang Liao, Jing Xiao, Junjun Jiang, Zheng Wang

Specifically, we propose to exploit the mutual information among them via iterative up-and-down projections, where the spatial and temporal features are fully fused and distilled, helping the high-quality video reconstruction.

Video Reconstruction Video Super-Resolution

Deep Quality Assessment of Compressed Videos: A Subjective and Objective Study

no code implementations7 May 2022 Liqun Lin, Zheng Wang, Jiachen He, Weiling Chen, Yiwen Xu, Tiesong Zhao

In this work, a semi-automatic labeling method is adopted to build a large-scale compressed video quality database, which allows us to label a large number of compressed videos with manageable human workload.

Video Quality Assessment Visual Question Answering +1

A Survey on Legal Judgment Prediction: Datasets, Metrics, Models and Challenges

no code implementations11 Apr 2022 Junyun Cui, Xiaoyu Shen, Feiping Nie, Zheng Wang, Jinglong Wang, Yulong Chen

In this paper, to address the current lack of comprehensive survey of existing LJP tasks, datasets, models and evaluations, (1) we analyze 31 LJP datasets in 6 languages, present their construction process and define a classification method of LJP with 3 different attributes; (2) we summarize 14 evaluation metrics under four categories for different outputs of LJP tasks; (3) we review 12 legal-domain pretrained models in 3 languages and highlight 3 major research directions for LJP; (4) we show the state-of-art results for 8 representative datasets from different court cases and discuss the open challenges.

Natural Language Processing

Unsupervised Manga Character Re-identification via Face-body and Spatial-temporal Associated Clustering

no code implementations10 Apr 2022 Zhimin Zhang, Zheng Wang, Wei Hu

In the past few years, there has been a dramatic growth in e-manga (electronic Japanese-style comics).

Exploring the Impact of Negative Samples of Contrastive Learning: A Case Study of Sentence Embedding

1 code implementation Findings (ACL) 2022 Rui Cao, Yihao Wang, Yuxin Liang, Ling Gao, Jie Zheng, Jie Ren, Zheng Wang

We define a maximum traceable distance metric, through which we learn to what extent the text contrastive learning benefits from the historical information of negative samples.

Contrastive Learning Sentence Embedding +2

Visual-tactile sensing for Real-time liquid Volume Estimation in Grasping

no code implementations23 Feb 2022 Fan Zhu, Ruixing Jia, Lei Yang, Youcan Yan, Zheng Wang, Jia Pan, Wenping Wang

We propose a deep visuo-tactile model for realtime estimation of the liquid inside a deformable container in a proprioceptive way. We fuse two sensory modalities, i. e., the raw visual inputs from the RGB camera and the tactile cues from our specific tactile sensor without any extra sensor calibrations. The robotic system is well controlled and adjusted based on the estimation model in real time.

Multi-Task Learning

Dynamic GPU Energy Optimization for Machine Learning Training Workloads

1 code implementation5 Jan 2022 Farui Wang, Weizhe Zhang, Shichao Lai, Meng Hao, Zheng Wang

This paper presents GPOEO, an online GPU energy optimization framework for machine learning training workloads.

Self-Adaptable Point Processes with Nonparametric Time Decays

no code implementations NeurIPS 2021 Zhimeng Pan, Zheng Wang, Jeff M. Phillips, Shandian Zhe

Specifically, we use an embedding to represent each event type and model the event influence as an unknown function of the embeddings and time span.

Point Processes

Both Style and Fog Matter: Cumulative Domain Adaptation for Semantic Foggy Scene Understanding

no code implementations CVPR 2022 Xianzheng Ma, Zhixiang Wang, Yacheng Zhan, Yinqiang Zheng, Zheng Wang, Dengxin Dai, Chia-Wen Lin

Unlike previous methods that mainly focus on closing the domain gap caused by fog -- defogging the foggy images or fogging the clear images, we propose to alleviate the domain gap by considering fog influence and style variation simultaneously.

Disentanglement Domain Adaptation +1

Stable and Compact Face Recognition via Unlabeled Data Driven Sparse Representation-Based Classification

no code implementations4 Nov 2021 XiaoHui Yang, Zheng Wang, Huan Wu, Licheng Jiao, Yiming Xu, Haolin Chen

The proposed model aims to mine the hidden semantic information and intrinsic structure information of all available data, which is suitable for few labeled samples and proportion imbalance between labeled samples and unlabeled samples problems in frontal face recognition.

Face Recognition Sparse Representation-based Classification

Optimizing Sparse Matrix Multiplications for Graph Neural Networks

no code implementations30 Oct 2021 Shenghao Qiu, You Liang, Zheng Wang

Our model is first trained offline using training matrix samples, and the trained model can be applied to any input matrix and GNN kernels with SpMM computation.

Nonparametric Sparse Tensor Factorization with Hierarchical Gamma Processes

no code implementations19 Oct 2021 Conor Tillinghast, Zheng Wang, Shandian Zhe

Compared with the existent works, our model not only leverages the structural information underlying the observed entry indices, but also provides extra interpretability and flexibility -- it can simultaneously estimate a set of location factors about the intrinsic properties of the tensor nodes, and another set of sociability factors reflecting their extrovert activity in interacting with others; users are free to choose a trade-off between the two types of factors.

Meta-Learning with Adjoint Methods

no code implementations16 Oct 2021 Shibo Li, Zheng Wang, Akil Narayan, Robert Kirby, Shandian Zhe

Despite its success, a critical challenge in MAML is to calculate the gradient w. r. t the initialization of a long training trajectory for the sampled tasks, because the computation graph can rapidly explode and the computational cost is very expensive.


GANet: Glyph-Attention Network for Few-Shot Font Generation

no code implementations29 Sep 2021 Mingtao Guo, Wei Xiong, Zheng Wang, Yong Tang, Ting Wu

Font generation is a valuable but challenging task, it is time consuming and costly to design font libraries which cover all glyphs with various styles.

Font Generation

Disentangled Implicit Shape and Pose Learning for Scalable 6D Pose Estimation

no code implementations27 Jul 2021 Yilin Wen, Xiangyu Li, Hao Pan, Lei Yang, Zheng Wang, Taku Komura, Wenping Wang

To handle multiple objects and generalize to unseen objects, we disentangle the latent object shape and pose representations, so that the latent shape space models shape similarities, and the latent pose code is used for rotation retrieval by comparison with canonical rotations.

6D Pose Estimation Metric Learning +1

Spectrum Gaussian Processes Based On Tunable Basis Functions

no code implementations14 Jul 2021 Wenqi Fang, Guanlin Wu, Jingjing Li, Zheng Wang, Jiang Cao, Yang Ping

Spectral approximation and variational inducing learning for the Gaussian process are two popular methods to reduce computational complexity.

Gaussian Processes

Reinforcement Learning-based Dialogue Guided Event Extraction to Exploit Argument Relations

1 code implementation23 Jun 2021 Qian Li, Hao Peng, JianXin Li, Jia Wu, Yuanxing Ning, Lihong Wang, Philip S. Yu, Zheng Wang

Our approach leverages knowledge of the already extracted arguments of the same sentence to determine the role of arguments that would be difficult to decide individually.

Event Extraction Incremental Learning +2

Effect of Adaptive and Fixed Shared Steering Control on Distracted Driver Behavior

no code implementations7 Jun 2021 Zheng Wang, Satoshi Suga, Edric John Cruz Nacpil, Bo Yang, Kimihiko Nakano

Evaluation results indicated that, for both attentive and distracted drivers, haptic guidance with adaptive authority yielded lower driver workload and reduced lane departure risk than manual driving and fixed authority.

Steering Control

Degrade is Upgrade: Learning Degradation for Low-light Image Enhancement

1 code implementation19 Mar 2021 Kui Jiang, Zhongyuan Wang, Zheng Wang, Chen Chen, Peng Yi, Tao Lu, Chia-Wen Lin

Different from existing methods tending to accomplish the relighting task directly by ignoring the fidelity and naturalness recovery, we investigate the intrinsic degradation and relight the low-light image while refining the details and color in two steps.

Low-Light Image Enhancement

A Reinforcement Learning Based R-Tree for Spatial Data Indexing in Dynamic Environments

no code implementations8 Mar 2021 Tu Gu, Kaiyu Feng, Gao Cong, Cheng Long, Zheng Wang, Sheng Wang

Learned indices have been proposed to replace classic index structures like B-Tree with machine learning (ML) models.


Model Rectification via Unknown Unknowns Extraction from Deployment Samples

no code implementations8 Feb 2021 Bruno Abrahao, Zheng Wang, Haider Ahmed, Yuchen Zhu

Model deficiency that results from incomplete training data is a form of structural blindness that leads to costly errors, oftentimes with high confidence.

Active Learning

Image Inpainting Guided by Coherence Priors of Semantics and Textures

no code implementations CVPR 2021 Liang Liao, Jing Xiao, Zheng Wang, Chia-Wen Lin, Shin'ichi Satoh

In this paper, we introduce coherence priors between the semantics and textures which make it possible to concentrate on completing separate textures in a semantic-wise manner.

Image Inpainting Semantic Segmentation

Re-identification = Retrieval + Verification: Back to Essence and Forward with a New Metric

1 code implementation23 Nov 2020 Zheng Wang, Xin Yuan, Toshihiko Yamasaki, Yutian Lin, Xin Xu, Wenjun Zeng

In essence, current re-ID overemphasizes the importance of retrieval but underemphasizes that of verification, \textit{i. e.}, all returned images are considered as the target.

Image Retrieval

Intention-Based Lane Changing and Lane Keeping Haptic Guidance Steering System

no code implementations15 Nov 2020 Zhanhong Yan, Kaiming Yang, Zheng Wang, Bo Yang, Tsutomu Kaizuka, Kimihiko Nakano

By exerting continuous torque on the steering wheel, both the driver and support system can share lateral control of the vehicle.

Steering Control

Towards Context-Aware Code Comment Generation

no code implementations Findings of the Association for Computational Linguistics 2020 Xiaohan Yu, Quzhe Huang, Zheng Wang, Yansong Feng, Dongyan Zhao

Code comments are vital for software maintenance and comprehension, but many software projects suffer from the lack of meaningful and up-to-date comments in practice.

Code Comment Generation Graph Attention

Learning Personalized Discretionary Lane-Change Initiation for Fully Autonomous Driving Based on Reinforcement Learning

no code implementations29 Oct 2020 Zhuoxi Liu, Zheng Wang, Bo Yang, Kimihiko Nakano

In this article, the authors present a novel method to learn the personalized tactic of discretionary lane-change initiation for fully autonomous vehicles through human-computer interactions.

Autonomous Driving reinforcement-learning

Universal Weighting Metric Learning for Cross-Modal Matching

1 code implementation CVPR 2020 Jiwei Wei, Xing Xu, Yang Yang, Yanli Ji, Zheng Wang, Heng Tao Shen

Furthermore, we introduce a new polynomial loss under the universal weighting framework, which defines a weight function for the positive and negative informative pairs respectively.

Metric Learning Text Matching

Uncertainty-aware Attention Graph Neural Network for Defending Adversarial Attacks

no code implementations22 Sep 2020 Boyuan Feng, Yuke Wang, Zheng Wang, Yufei Ding

With the increasing popularity of graph-based learning, graph neural networks (GNNs) emerge as the essential tool for gaining insights from graphs.

DTDN: Dual-task De-raining Network

1 code implementation21 Aug 2020 Zheng Wang, Jianwu Li, Ge Song

Removing rain streaks from rainy images is necessary for many tasks in computer vision, such as object detection and recognition.

object-detection Object Detection +1

Towards Unsupervised Crowd Counting via Regression-Detection Bi-knowledge Transfer

no code implementations12 Aug 2020 Yuting Liu, Zheng Wang, Miaojing Shi, Shin'ichi Satoh, Qijun Zhao, Hongyu Yang

We formulate the mutual transformations between the outputs of regression- and detection-based models as two scene-agnostic transformers which enable knowledge distillation between the two models.

Crowd Counting Knowledge Distillation +2

Lifelong Property Price Prediction: A Case Study for the Toronto Real Estate Market

no code implementations12 Aug 2020 Hao Peng, Jian-Xin Li, Zheng Wang, Renyu Yang, Mingzhe Liu, Mingming Zhang, Philip S. Yu, Lifang He

As a departure from prior work, Luce organizes the house data in a heterogeneous information network (HIN) where graph nodes are house entities and attributes that are important for house price valuation.

3D Spectrum Mapping Based on ROI-Driven UAV Deployment

no code implementations6 Aug 2020 Qihui Wu, Feng Shen, Zheng Wang, Guoru Ding

Given the explosive growth of Internet of Things (IoT) devices ranging from the two-dimensional (2D) ground to the three-dimensional (3D) space, it is a necessity to establish a 3D spectrum map to comprehensively present and effectively manage the 3D spatial spectrum resources in smart city infrastructures.

Exploring Image Enhancement for Salient Object Detection in Low Light Images

no code implementations31 Jul 2020 Xin Xu, Shiqin Wang, Zheng Wang, Xiaolong Zhang, Ruimin Hu

Low light images captured in a non-uniform illumination environment usually are degraded with the scene depth and the corresponding environment lights.

Image Enhancement object-detection +2

Streaming Probabilistic Deep Tensor Factorization

no code implementations14 Jul 2020 Shikai Fang, Zheng Wang, Zhimeng Pan, Ji Liu, Shandian Zhe

Our algorithm provides responsive incremental updates for the posterior of the latent factors and NN weights upon receiving new tensor entries, and meanwhile select and inhibit redundant/useless weights.

Network Embedding with Completely-imbalanced Labels

2 code implementations IEEE Transactions on Knowledge and Data Engineering 2020 Zheng Wang, Xiaojun Ye, Chaokun Wang, Jian Cui, Philip S. Yu

Network embedding, aiming to project a network into a low-dimensional space, is increasingly becoming a focus of network research.

Network Embedding

Road Network Metric Learning for Estimated Time of Arrival

no code implementations24 Jun 2020 Yiwen Sun, Kun fu, Zheng Wang, Chang-Shui Zhang, Jieping Ye

To address the data sparsity problem, we propose the Road Network Metric Learning framework for ETA (RNML-ETA).

Metric Learning

Sparse Gaussian Process Based On Hat Basis Functions

no code implementations15 Jun 2020 Wenqi Fang, Huiyun Li, Hui Huang, Shaobo Dang, Zhejun Huang, Zheng Wang

Based on hat basis functions, we propose a new sparse Gaussian process method to solve the unconstrained regression problem.

Physics Informed Deep Kernel Learning

no code implementations8 Jun 2020 Zheng Wang, Wei Xing, Robert Kirby, Shandian Zhe

Deep kernel learning is a promising combination of deep neural networks and nonparametric function learning.

Gaussian Processes

Multi-Fidelity High-Order Gaussian Processes for Physical Simulation

1 code implementation8 Jun 2020 Zheng Wang, Wei Xing, Robert Kirby, Shandian Zhe

To address these issues, we propose Multi-Fidelity High-Order Gaussian Process (MFHoGP) that can capture complex correlations both between the outputs and between the fidelities to enhance solution estimation, and scale to large numbers of outputs.

Gaussian Processes

Fusion Recurrent Neural Network

no code implementations7 Jun 2020 Yiwen Sun, Yulu Wang, Kun fu, Zheng Wang, Chang-Shui Zhang, Jieping Ye

Furthermore, in order to evaluate Fusion RNN's sequence feature extraction capability, we choose a representative data mining task for sequence data, estimated time of arrival (ETA) and present a novel model based on Fusion RNN.

FMA-ETA: Estimating Travel Time Entirely Based on FFN With Attention

no code implementations7 Jun 2020 Yiwen Sun, Yulu Wang, Kun fu, Zheng Wang, Ziang Yan, Chang-Shui Zhang, Jieping Ye

Estimated time of arrival (ETA) is one of the most important services in intelligent transportation systems and becomes a challenging spatial-temporal (ST) data mining task in recent years.

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

Constructing Geographic and Long-term Temporal Graph for Traffic Forecasting

no code implementations23 Apr 2020 Yiwen Sun, Yulu Wang, Kun fu, Zheng Wang, Chang-Shui Zhang, Jieping Ye

Recently, deep learning based methods have achieved promising results by adopting graph convolutional network (GCN) to extract the spatial correlations and recurrent neural network (RNN) to capture the temporal dependencies.

Efficient and Effective Similar Subtrajectory Search with Deep Reinforcement Learning

no code implementations5 Mar 2020 Zheng Wang, Cheng Long, Gao Cong, Yiding Liu

Similar trajectory search is a fundamental problem and has been well studied over the past two decades.


Optimizing Streaming Parallelism on Heterogeneous Many-Core Architectures: A Machine Learning Based Approach

1 code implementation5 Mar 2020 Peng Zhang, Jianbin Fang, Canqun Yang, Chun Huang, Tao Tang, Zheng Wang

This article presents an automatic approach to quickly derive a good solution for hardware resource partition and task granularity for task-based parallel applications on heterogeneous many-core architectures.

Robotic Cane as a Soft SuperLimb for Elderly Sit-to-Stand Assistance

no code implementations29 Feb 2020 Xia Wu, Haiyuan Liu, Ziqi Liu, Mingdong Chen, Fang Wan, Chenglong Fu, Harry Asada, Zheng Wang, Chaoyang Song

Many researchers have identified robotics as a potential solution to the aging population faced by many developed and developing countries.

Curriculum Audiovisual Learning

no code implementations26 Jan 2020 Di Hu, Zheng Wang, Haoyi Xiong, Dong Wang, Feiping Nie, Dejing Dou

Associating sound and its producer in complex audiovisual scene is a challenging task, especially when we are lack of annotated training data.

Learning Canonical Shape Space for Category-Level 6D Object Pose and Size Estimation

no code implementations CVPR 2020 Dengsheng Chen, Jun Li, Zheng Wang, Kai Xu

To tackle intra-class shape variations, we learn canonical shape space (CASS), a unified representation for a large variety of instances of a certain object category.

3D Shape Representation Generating 3D Point Clouds

Characterizing Scalability of Sparse Matrix-Vector Multiplications on Phytium FT-2000+ Many-cores

no code implementations20 Nov 2019 Donglin Chen, Jianbin Fang, Chuanfu Xu, Shizhao Chen, Zheng Wang

Understanding the scalability of parallel programs is crucial for software optimization and hardware architecture design.

Optimizing Deep Learning Inference on Embedded Systems Through Adaptive Model Selection

no code implementations9 Nov 2019 Vicent Sanz Marco, Ben Taylor, Zheng Wang, Yehia Elkhatib

For image classification, we achieve a 1. 8x reduction in inference time with a 7. 52% improvement in accuracy, over the most-capable single DNN model.

Image Classification Machine Translation +2

BAIL: Best-Action Imitation Learning for Batch Deep Reinforcement Learning

1 code implementation NeurIPS 2020 Xinyue Chen, Zijian Zhou, Zheng Wang, Che Wang, Yanqiu Wu, Keith Ross

There has recently been a surge in research in batch Deep Reinforcement Learning (DRL), which aims for learning a high-performing policy from a given dataset without additional interactions with the environment.

Imitation Learning Q-Learning +1

Conditional Expectation Propagation

no code implementations27 Oct 2019 Zheng Wang, Shandian Zhe

Expectation propagation (EP) is a powerful approximate inference algorithm.

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

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

Zero-Shot Feature Selection via Transferring Supervised Knowledge

no code implementations9 Aug 2019 Zheng Wang, Qiao Wang, Tingzhang Zhao, Xiaojun Ye

Feature selection, an effective technique for dimensionality reduction, plays an important role in many machine learning systems.

Dimensionality Reduction feature selection +1

Robust Linear Discriminant Analysis Using Ratio Minimization of L1,2-Norms

no code implementations29 Jun 2019 Feiping Nie, Hua Wang, Zheng Wang, Heng Huang

In this paper, we propose a novel robust linear discriminant analysis method based on the L1, 2-norm ratio minimization.

Beyond Intra-modality: A Survey of Heterogeneous Person Re-identification

no code implementations24 May 2019 Zheng Wang, Zhixiang Wang, Yinqiang Zheng, Yang Wu, Wen-Jun Zeng, Shin'ichi Satoh

An efficient and effective person re-identification (ReID) system relieves the users from painful and boring video watching and accelerates the process of video analysis.

Person Re-Identification

Less Memory, Faster Speed: Refining Self-Attention Module for Image Reconstruction

no code implementations20 May 2019 Zheng Wang, Jianwu Li, Ge Song, Tieling Li

Self-attention (SA) mechanisms can capture effectively global dependencies in deep neural networks, and have been applied to natural language processing and image processing successfully.

Image Reconstruction Natural Language Processing

DotSCN: Group Re-identification via Domain-Transferred Single and Couple Representation Learning

no code implementations13 May 2019 Ziling Huang, Zheng Wang, Chung-Chi Tsai, Shin'ichi Satoh, Chia-Wen Lin

To gain the superiority of deep learning models, we treat a group as multiple persons and transfer the domain of a labeled ReID dataset to a G-ReID target dataset style to learn single representations.

Person Re-Identification Representation Learning

Ensemble Super-Resolution with A Reference Dataset

1 code implementation12 May 2019 Junjun Jiang, Yi Yu, Zheng Wang, Suhua Tang, Ruimin Hu, Jiayi Ma

In this paper, we present a simple but effective single image SR method based on ensemble learning, which can produce a better performance than that could be obtained from any of SR methods to be ensembled (or called component super-resolvers).

Ensemble Learning Image Super-Resolution

Illumination-Adaptive Person Re-identification

no code implementations11 May 2019 Zelong Zeng, Zhixiang Wang, Zheng Wang, Yinqiang Zheng, Yung-Yu Chuang, Shin'ichi Satoh

To demonstrate the illumination issue and to evaluate our model, we construct two large-scale simulated datasets with a wide range of illumination variations.

Disentanglement Person Re-Identification +1

Robust Semantic Segmentation By Dense Fusion Network On Blurred VHR Remote Sensing Images

no code implementations7 Mar 2019 Yi Peng, Shihao Sun, Zheng Wang, Yining Pan, Ruirui Li

Robust semantic segmentation of VHR remote sensing images from UAV sensors is critical for earth observation, land use, land cover or mapping applications.

Semantic Segmentation

Interaction-aware Kalman Neural Networks for Trajectory Prediction

no code implementations28 Feb 2019 Ce Ju, Zheng Wang, Cheng Long, Xiao-Yu Zhang, Gao Cong, Dong Eui Chang

Forecasting the motion of surrounding obstacles (vehicles, bicycles, pedestrians and etc.)

Robotics I.2.9; I.2.0

Lattice CNNs for Matching Based Chinese Question Answering

1 code implementation25 Feb 2019 Yuxuan Lai, Yansong Feng, Xiaohan Yu, Zheng Wang, Kun Xu, Dongyan Zhao

Short text matching often faces the challenges that there are great word mismatch and expression diversity between the two texts, which would be further aggravated in languages like Chinese where there is no natural space to segment words explicitly.

Question Answering Text Matching

Representation Learning for Spatial Graphs

no code implementations17 Dec 2018 Zheng Wang, Ce Ju, Gao Cong, Cheng Long

Recently, the topic of graph representation learning has received plenty of attention.

Denoising Graph Representation Learning

Global and Local Sensitivity Guided Key Salient Object Re-augmentation for Video Saliency Detection

no code implementations19 Nov 2018 Ziqi Zhou, Zheng Wang, Huchuan Lu, Song Wang, Meijun Sun

In this paper, based on the fact that salient areas in videos are relatively small and concentrated, we propose a \textbf{key salient object re-augmentation method (KSORA) using top-down semantic knowledge and bottom-up feature guidance} to improve detection accuracy in video scenes.

Decision Making feature selection +1

Composite Binary Decomposition Networks

no code implementations16 Nov 2018 You Qiaoben, Zheng Wang, Jianguo Li, Yinpeng Dong, Yu-Gang Jiang, Jun Zhu

Binary neural networks have great resource and computing efficiency, while suffer from long training procedure and non-negligible accuracy drops, when comparing to the full-precision counterparts.

General Classification Image Classification +3

To Compress, or Not to Compress: Characterizing Deep Learning Model Compression for Embedded Inference

no code implementations21 Oct 2018 Qing Qin, Jie Ren, Jialong Yu, Ling Gao, Hai Wang, Jie Zheng, Yansong Feng, Jianbin Fang, Zheng Wang

We experimentally show that how two mainstream compression techniques, data quantization and pruning, perform on these network architectures and the implications of compression techniques to the model storage size, inference time, energy consumption and performance metrics.

Image Classification Model Compression +2

SG-FCN: A Motion and Memory-Based Deep Learning Model for Video Saliency Detection

no code implementations21 Sep 2018 Meijun Sun, Ziqi Zhou, QinGhua Hu, Zheng Wang, Jianmin Jiang

To this end, we propose a novel and efficient video eye fixation detection model to improve the saliency detection performance.

Video Saliency Detection

Socially Aware Kalman Neural Networks for Trajectory Prediction

no code implementations14 Sep 2018 Ce Ju, Zheng Wang, Xiao-Yu Zhang

Trajectory prediction is a critical technique in the navigation of robots and autonomous vehicles.

Autonomous Vehicles Trajectory Prediction

Hyperspectral Image Classification in the Presence of Noisy Labels

1 code implementation12 Sep 2018 Junjun Jiang, Jiayi Ma, Zheng Wang, Chen Chen, Xian-Ming Liu

The key idea of RLPA is to exploit knowledge (e. g., the superpixel based spectral-spatial constraints) from the observed hyperspectral images and apply it to the process of label propagation.

Classification General Classification +1

Marrying up Regular Expressions with Neural Networks: A Case Study for Spoken Language Understanding

no code implementations ACL 2018 Bingfeng Luo, Yansong Feng, Zheng Wang, Songfang Huang, Rui Yan, Dongyan Zhao

The success of many natural language processing (NLP) tasks is bound by the number and quality of annotated data, but there is often a shortage of such training data.

Intent Detection Natural Language Processing +2

Adaptive Selection of Deep Learning Models on Embedded Systems

no code implementations11 May 2018 Ben Taylor, Vicent Sanz Marco, Willy Wolff, Yehia Elkhatib, Zheng Wang

This paper presents an adaptive scheme to determine which DNN model to use for a given input, by considering the desired accuracy and inference time.

Image Classification

Machine Learning in Compiler Optimisation

no code implementations9 May 2018 Zheng Wang, Michael O'Boyle

In the last decade, machine learning based compilation has moved from an an obscure research niche to a mainstream activity.

Tuning Streamed Applications on Intel Xeon Phi: A Machine Learning Based Approach

no code implementations8 Feb 2018 Peng Zhang, Jianbin Fang, Tao Tang, Canqun Yang, Zheng Wang

In this paper, we present an automatic approach to determine the hardware resource partition and the task granularity for any given application, targeting the Intel XeonPhi architecture.


Scale Up Event Extraction Learning via Automatic Training Data Generation

no code implementations11 Dec 2017 Ying Zeng, Yansong Feng, Rong Ma, Zheng Wang, Rui Yan, Chongde Shi, Dongyan Zhao

We show that this large volume of training data not only leads to a better event extractor, but also allows us to detect multiple typed events.

Event Extraction

Equivalence between LINE and Matrix Factorization

no code implementations19 Jul 2017 Qiao Wang, Zheng Wang, Xiaojun Ye

LINE [1], as an efficient network embedding method, has shown its effectiveness in dealing with large-scale undirected, directed, and/or weighted networks.

Network Embedding

Efficient Delivery Policy to Minimize User Traffic Consumption in Guaranteed Advertising

no code implementations23 Nov 2016 Jia Zhang, Zheng Wang, Qian Li, Jialin Zhang, Yanyan Lan, Qiang Li, Xiaoming Sun

In the guaranteed delivery scenario, ad exposures (which are also called impressions in some works) to users are guaranteed by contracts signed in advance between advertisers and publishers.

An expanded evaluation of protein function prediction methods shows an improvement in accuracy

1 code implementation3 Jan 2016 Yuxiang Jiang, Tal Ronnen Oron, Wyatt T Clark, Asma R Bankapur, Daniel D'Andrea, Rosalba Lepore, Christopher S Funk, Indika Kahanda, Karin M Verspoor, Asa Ben-Hur, Emily Koo, Duncan Penfold-Brown, Dennis Shasha, Noah Youngs, Richard Bonneau, Alexandra Lin, Sayed ME Sahraeian, Pier Luigi Martelli, Giuseppe Profiti, Rita Casadio, Renzhi Cao, Zhaolong Zhong, Jianlin Cheng, Adrian Altenhoff, Nives Skunca, Christophe Dessimoz, Tunca Dogan, Kai Hakala, Suwisa Kaewphan, Farrokh Mehryary, Tapio Salakoski, Filip Ginter, Hai Fang, Ben Smithers, Matt Oates, Julian Gough, Petri Törönen, Patrik Koskinen, Liisa Holm, Ching-Tai Chen, Wen-Lian Hsu, Kevin Bryson, Domenico Cozzetto, Federico Minneci, David T Jones, Samuel Chapman, Dukka B K. C., Ishita K Khan, Daisuke Kihara, Dan Ofer, Nadav Rappoport, Amos Stern, Elena Cibrian-Uhalte, Paul Denny, Rebecca E Foulger, Reija Hieta, Duncan Legge, Ruth C Lovering, Michele Magrane, Anna N Melidoni, Prudence Mutowo-Meullenet, Klemens Pichler, Aleksandra Shypitsyna, Biao Li, Pooya Zakeri, Sarah ElShal, Léon-Charles Tranchevent, Sayoni Das, Natalie L Dawson, David Lee, Jonathan G Lees, Ian Sillitoe, Prajwal Bhat, Tamás Nepusz, Alfonso E Romero, Rajkumar Sasidharan, Haixuan Yang, Alberto Paccanaro, Jesse Gillis, Adriana E Sedeño-Cortés, Paul Pavlidis, Shou Feng, Juan M Cejuela, Tatyana Goldberg, Tobias Hamp, Lothar Richter, Asaf Salamov, Toni Gabaldon, Marina Marcet-Houben, Fran Supek, Qingtian Gong, Wei Ning, Yuanpeng Zhou, Weidong Tian, Marco Falda, Paolo Fontana, Enrico Lavezzo, Stefano Toppo, Carlo Ferrari, Manuel Giollo, Damiano Piovesan, Silvio Tosatto, Angela del Pozo, José M Fernández, Paolo Maietta, Alfonso Valencia, Michael L Tress, Alfredo Benso, Stefano Di Carlo, Gianfranco Politano, Alessandro Savino, Hafeez Ur Rehman, Matteo Re, Marco Mesiti, Giorgio Valentini, Joachim W Bargsten, Aalt DJ van Dijk, Branislava Gemovic, Sanja Glisic, Vladmir Perovic, Veljko Veljkovic, Nevena Veljkovic, Danillo C Almeida-e-Silva, Ricardo ZN Vencio, Malvika Sharan, Jörg Vogel, Lakesh Kansakar, Shanshan Zhang, Slobodan Vucetic, Zheng Wang, Michael JE Sternberg, Mark N Wass, Rachael P Huntley, Maria J Martin, Claire O'Donovan, Peter N. Robinson, Yves Moreau, Anna Tramontano, Patricia C Babbitt, Steven E Brenner, Michal Linial, Christine A Orengo, Burkhard Rost, Casey S Greene, Sean D Mooney, Iddo Friedberg, Predrag Radivojac

To review progress in the field, the analysis also compared the best methods participating in CAFA1 to those of CAFA2.

Quantitative Methods

Orthogonal Rank-One Matrix Pursuit for Low Rank Matrix Completion

1 code implementation4 Apr 2014 Zheng Wang, Ming-Jun Lai, Zhaosong Lu, Wei Fan, Hasan Davulcu, Jieping Ye

Numerical results show that our proposed algorithm is more efficient than competing algorithms while achieving similar or better prediction performance.

Low-Rank Matrix Completion

UPPAAL-SMC: Statistical Model Checking for Priced Timed Automata

no code implementations4 Jul 2012 Peter Bulychev, Alexandre David, Kim Gulstrand Larsen, Marius Mikučionis, Danny Bøgsted Poulsen, Axel Legay, Zheng Wang

The focus of the survey is on the evolution of the tool - including modeling and specification formalisms as well as techniques applied - together with applications of the tool to case studies.

Logic in Computer Science Formal Languages and Automata Theory

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