Search Results for author: Zheng Wang

Found 150 papers, 54 papers with code

An Effective Two-stage Training Paradigm Detector for Small Dataset

no code implementations11 Sep 2023 Zheng Wang, Dong Xie, Hanzhi Wang, Jiang Tian

Learning from the limited amount of labeled data to the pre-train model has always been viewed as a challenging task.

object-detection Object Detection

Uncovering the Unseen: Discover Hidden Intentions by Micro-Behavior Graph Reasoning

no code implementations29 Aug 2023 Zhuo Zhou, Wenxuan Liu, Danni Xu, Zheng Wang, Jian Zhao

HID presents a unique challenge in that hidden intentions lack the obvious visual representations to distinguish them from normal intentions.

Intent Detection

A Survey of Diffusion Based Image Generation Models: Issues and Their Solutions

no code implementations25 Aug 2023 Tianyi Zhang, Zheng Wang, Jing Huang, Mohiuddin Muhammad Tasnim, Wei Shi

Fortunately, the availability of open-source stable diffusion models and their underlying mathematical principles has enabled the academic community to extensively analyze the performance of current image generation models and make improvements based on this stable diffusion framework.

Image Generation

A Generalized Physical-knowledge-guided Dynamic Model for Underwater Image Enhancement

no code implementations10 Aug 2023 Pan Mu, Hanning Xu, Zheyuan Liu, Zheng Wang, Sixian Chan, Cong Bai

To tackle these challenges, we design a Generalized Underwater image enhancement method via a Physical-knowledge-guided Dynamic Model (short for GUPDM), consisting of three parts: Atmosphere-based Dynamic Structure (ADS), Transmission-guided Dynamic Structure (TDS), and Prior-based Multi-scale Structure (PMS).

Image Enhancement

NNVISR: Bring Neural Network Video Interpolation and Super Resolution into Video Processing Framework

1 code implementation6 Aug 2023 Yuan Tong, Mengshun Hu, Zheng Wang

We present NNVISR - an open-source filter plugin for the VapourSynth video processing framework, which facilitates the application of neural networks for various kinds of video enhancing tasks, including denoising, super resolution, interpolation, and spatio-temporal super-resolution.

Denoising Super-Resolution +1

From Generation to Suppression: Towards Effective Irregular Glow Removal for Nighttime Visibility Enhancement

no code implementations31 Jul 2023 Wanyu Wu, Wei Wang, Zheng Wang, Kui Jiang, Xin Xu

Most existing Low-Light Image Enhancement (LLIE) methods are primarily designed to improve brightness in dark regions, which suffer from severe degradation in nighttime images.

Low-Light Image Enhancement Zero-Shot Learning

Revisiting Domain-Adaptive 3D Object Detection by Reliable, Diverse and Class-balanced Pseudo-Labeling

1 code implementation16 Jul 2023 Zhuoxiao Chen, Yadan Luo, Zheng Wang, Mahsa Baktashmotlagh, Zi Huang

Unsupervised domain adaptation (DA) with the aid of pseudo labeling techniques has emerged as a crucial approach for domain-adaptive 3D object detection.

3D Object Detection object-detection +1

TransRef: Multi-Scale Reference Embedding Transformer for Reference-Guided Image Inpainting

1 code implementation20 Jun 2023 Liang Liao, Taorong Liu, Delin Chen, Jing Xiao, Zheng Wang, Chia-Wen Lin, Shin'ichi Satoh

For precise utilization of the reference features for guidance, a reference-patch alignment (Ref-PA) module is proposed to align the patch features of the reference and corrupted images and harmonize their style differences, while a reference-patch transformer (Ref-PT) module is proposed to refine the embedded reference feature.

Image Inpainting Image Restoration

Spatial-Temporal Graph Learning with Adversarial Contrastive Adaptation

1 code implementation19 Jun 2023 Qianru Zhang, Chao Huang, Lianghao Xia, Zheng Wang, SiuMing Yiu, Ruihua Han

In addition, we introduce a cross-view contrastive learning paradigm to model the inter-dependencies across view-specific region representations and preserve underlying relation heterogeneity.

Contrastive Learning Graph Learning +1

One for All: Unified Workload Prediction for Dynamic Multi-tenant Edge Cloud Platforms

1 code implementation2 Jun 2023 Shaoyuan Huang, Zheng Wang, Heng Zhang, Xiaofei Wang, Cheng Zhang, Wenyu Wang

In this paper, we propose an end-to-end framework with global pooling and static content awareness, DynEformer, to provide a unified workload prediction scheme for dynamic MT-ECP.

Time Series Time Series Prediction

Group Activity Recognition via Dynamic Composition and Interaction

no code implementations9 May 2023 Youliang Zhang, Zhuo Zhou, Wenxuan Liu, Danni Xu, Zheng Wang

Group composition tells us the location of people and their relations inside the group, while interaction reflects the relation between humans and objects outside the group.

Group Activity Recognition Human-Object Interaction Detection

Automated Spatio-Temporal Graph Contrastive Learning

1 code implementation6 May 2023 Qianru Zhang, Chao Huang, Lianghao Xia, Zheng Wang, Zhonghang Li, SiuMing Yiu

In this paper, we tackle the above challenges by exploring the Automated Spatio-Temporal graph contrastive learning paradigm (AutoST) over the heterogeneous region graph generated from multi-view data sources.

Contrastive Learning

ScanERU: Interactive 3D Visual Grounding based on Embodied Reference Understanding

1 code implementation23 Mar 2023 Ziyang Lu, Yunqiang Pei, Guoqing Wang, Yang Yang, Zheng Wang, Heng Tao Shen

Despite their effectiveness, existing methods suffer from the difficulty of low recognition accuracy in cases of multiple adjacent objects with similar appearances. To address this issue, this work intuitively introduces the human-robot interaction as a cue to facilitate the development of 3D visual grounding.

Visual Grounding

Adaptive Modeling of Uncertainties for Traffic Forecasting

no code implementations16 Mar 2023 Ying Wu, Yongchao Ye, Adnan Zeb, James J. Q. Yu, Zheng Wang

We evaluated QuanTraffic by applying it to five representative DNN models for traffic forecasting across seven public datasets.

Management Traffic Prediction

Good Is Bad: Causality Inspired Cloth-Debiasing for Cloth-Changing Person Re-Identification

1 code implementation CVPR 2023 Zhengwei Yang, Meng Lin, Xian Zhong, Yu Wu, Zheng Wang

Entangled representation of clothing and identity (ID)-intrinsic clues are potentially concomitant in conventional person Re-IDentification (ReID).

Person Re-Identification

Multilateral Semantic Relations Modeling for Image Text Retrieval

no code implementations CVPR 2023 Zheng Wang, Zhenwei Gao, Kangshuai Guo, Yang Yang, Xiaoming Wang, Heng Tao Shen

Specifically, a given query is first mapped as a probabilistic embedding to learn its true semantic distribution based on Mahalanobis distance.

Retrieval Text Retrieval

Error-aware Quantization through Noise Tempering

no code implementations11 Dec 2022 Zheng Wang, Juncheng B Li, Shuhui Qu, Florian Metze, Emma Strubell

In this work, we incorporate exponentially decaying quantization-error-aware noise together with a learnable scale of task loss gradient to approximate the effect of a quantization operator.

Model Compression Quantization

Prototypical Residual Networks for Anomaly Detection and Localization

no code implementations CVPR 2023 HUI ZHANG, Zuxuan Wu, Zheng Wang, Zhineng Chen, Yu-Gang Jiang

Anomaly detection and localization are widely used in industrial manufacturing for its efficiency and effectiveness.

Ranked #2 on Supervised Anomaly Detection on MVTec AD (using extra training data)

Supervised Anomaly Detection

Instance-level Heterogeneous Domain Adaptation for Limited-labeled Sketch-to-Photo Retrieval

1 code implementation IEEE Transactions on Multimedia 2020 Fan Yang, Yang Wu, Zheng Wang, Xiang Li, Sakriani Sakti, Satoshi Nakamura

Therefore, previous works pre-train their models on rich-labeled photo retrieval data (i. e., source domain) and then fine-tune them on the limited-labeled sketch-to-photo retrieval data (i. e., target domain).

Domain Adaptation Image Retrieval +1

FedGS: Federated Graph-based Sampling with Arbitrary Client Availability

1 code implementation25 Nov 2022 Zheng Wang, Xiaoliang Fan, Jianzhong Qi, Haibing Jin, Peizhen Yang, Siqi Shen, Cheng Wang

Second, constrained by the far-distance in data distribution of the sampled clients, we further minimize the variance of the numbers of times that the clients are sampled, to mitigate long-term bias.

Federated Learning

On Inferring User Socioeconomic Status with Mobility Records

1 code implementation15 Nov 2022 Zheng Wang, Mingrui Liu, Cheng Long, Qianru Zhang, Jiangneng Li, Chunyan Miao

The DeepSEI model incorporates two networks called deep network and recurrent network, which extract the features of the mobility records from three aspects, namely spatiality, temporality and activity, one at a coarse level and the other at a detailed level.


UmeTrack: Unified multi-view end-to-end hand tracking for VR

no code implementations31 Oct 2022 Shangchen Han, Po-Chen Wu, Yubo Zhang, Beibei Liu, Linguang Zhang, Zheng Wang, Weiguang Si, Peizhao Zhang, Yujun Cai, Tomas Hodan, Randi Cabezas, Luan Tran, Muzaffer Akbay, Tsz-Ho Yu, Cem Keskin, Robert Wang

In this paper, we present a unified end-to-end differentiable framework for multi-view, multi-frame hand tracking that directly predicts 3D hand pose in world space.

Context-Enhanced Stereo Transformer

1 code implementation21 Oct 2022 Weiyu Guo, Zhaoshuo Li, Yongkui Yang, Zheng Wang, Russell H. Taylor, Mathias Unberath, Alan Yuille, Yingwei Li

We construct our stereo depth estimation model, Context Enhanced Stereo Transformer (CSTR), by plugging CEP into the state-of-the-art stereo depth estimation method Stereo Transformer.

Stereo Depth Estimation Stereo Matching

A Survey of Data Optimization for Problems in Computer Vision Datasets

1 code implementation21 Oct 2022 Zhijing Wan, Zhixiang Wang, CheukTing Chung, Zheng Wang

Next, we organize these data optimization works according to data problems addressed, and provide a systematic and comparative description.

Active Learning

SQuAT: Sharpness- and Quantization-Aware Training for BERT

no code implementations13 Oct 2022 Zheng Wang, Juncheng B Li, Shuhui Qu, Florian Metze, Emma Strubell

Quantization is an effective technique to reduce memory footprint, inference latency, and power consumption of deep learning models.


Physical Adversarial Attack meets Computer Vision: A Decade Survey

1 code implementation30 Sep 2022 Hui Wei, Hao Tang, Xuemei Jia, Hanxun Yu, Zhubo Li, Zhixiang Wang, Shin'ichi Satoh, Zheng Wang

Although Deep Neural Networks (DNNs) have achieved impressive results in computer vision, their exposed vulnerability to adversarial attacks remains a serious concern.

Adversarial Attack Medical Diagnosis

Faith: An Efficient Framework for Transformer Verification on GPUs

1 code implementation23 Sep 2022 Boyuan Feng, Tianqi Tang, yuke wang, Zhaodong Chen, Zheng Wang, Shu Yang, Yuan Xie, Yufei Ding

In this paper, we propose Faith, an efficient framework for transformer verification on GPUs.

MGG: Accelerating Graph Neural Networks with Fine-grained intra-kernel Communication-Computation Pipelining on Multi-GPU Platforms

1 code implementation14 Sep 2022 yuke wang, Boyuan Feng, Zheng Wang, Tong Geng, Kevin Barker, Ang Li, Yufei Ding

For irregularly sparse and fine-grained GNN workloads, such solutions miss the opportunity to jointly schedule/optimize the computation and communication operations for high-performance delivery.

Layout Design Management

Detecting Algorithmically Generated Domains Using a GCNN-LSTM Hybrid Neural Network

no code implementations6 Aug 2022 Zheng Wang

Domain generation algorithm (DGA) is used by botnets to build a stealthy command and control (C&C) communication channel between the C&C server and the bots.

Understanding Adversarial Robustness of Vision Transformers via Cauchy Problem

1 code implementation1 Aug 2022 Zheng Wang, Wenjie Ruan

Recent research on the robustness of deep learning has shown that Vision Transformers (ViTs) surpass the Convolutional Neural Networks (CNNs) under some perturbations, e. g., natural corruption, adversarial attacks, etc.

Adversarial Robustness

Reference-Guided Texture and Structure Inference for Image Inpainting

1 code implementation29 Jul 2022 Taorong Liu, Liang Liao, Zheng Wang, Shin'ichi Satoh

Existing learning-based image inpainting methods are still in challenge when facing complex semantic environments and diverse hole patterns.

Image Inpainting

Magic ELF: Image Deraining Meets Association Learning and Transformer

1 code implementation21 Jul 2022 Kui Jiang, Zhongyuan Wang, Chen Chen, Zheng Wang, Laizhong Cui, Chia-Wen Lin

Convolutional neural network (CNN) and Transformer have achieved great success in multimedia applications.

Rain Removal

You Only Align Once: Bidirectional Interaction for Spatial-Temporal Video Super-Resolution

no code implementations13 Jul 2022 Mengshun Hu, Kui Jiang, Zhixiang Nie, Zheng Wang

Spatial-Temporal Video Super-Resolution (ST-VSR) technology generates high-quality videos with higher resolution and higher frame rates.

Video Super-Resolution

Nonparametric Factor Trajectory Learning for Dynamic Tensor Decomposition

no code implementations6 Jul 2022 Zheng Wang, Shandian Zhe

In practice, tensor data is often accompanied by temporal information, namely the time points when the entry values were generated.

Tensor Decomposition

Infinite-Fidelity Coregionalization for Physical Simulation

no code implementations1 Jul 2022 Shibo Li, Zheng Wang, Robert M. Kirby, Shandian Zhe

Our model can interpolate and/or extrapolate the predictions to novel fidelities, which can be even higher than the fidelities of training data.

Gaussian Processes

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 Pseudo Label +4

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

1 code implementation22 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 +1

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 (VQA)

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.

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 +3

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.

BIG-bench Machine Learning Scheduling

TC-GNN: Bridging Sparse GNN Computation and Dense Tensor Cores on GPUs

2 code implementations3 Dec 2021 yuke wang, Boyuan Feng, Zheng Wang, Guyue Huang, Yufei Ding

Recently, graph neural networks (GNNs), as the backbone of graph-based machine learning, demonstrate great success in various domains (e. g., e-commerce).


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

the initialization, we only need to run the standard ODE solver twice -- one is forward in time that evolves a long trajectory of gradient flow for the sampled task; the other is backward and solves the adjoint ODE.


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

DISP6D: Disentangled Implicit Shape and Pose Learning for Scalable 6D Pose Estimation

1 code implementation27 Jul 2021 Yilin Wen, Xiangyu Li, Hao Pan, Lei Yang, Zheng Wang, Taku Komura, Wenping Wang

Scalable 6D pose estimation for rigid objects from RGB images aims at handling multiple objects and generalizing to novel objects.

6D Pose Estimation Metric Learning +2

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

Automated Timeline Length Selection for Flexible Timeline Summarization

no code implementations29 May 2021 Xi Li, Qianren Mao, Hao Peng, Hongdong Zhu, JianXin Li, Zheng Wang

This paper presents a better TLS approach for automatically and dynamically determining the TLS timeline length.

Information Retrieval Retrieval +3

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

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 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 Comment Generation +1

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 (RL)

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.

Image-text matching Metric Learning +1

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 +3

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

1 code implementation12 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

1 code implementation14 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 Vocal Bursts Intensity Prediction

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.

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.

BIG-bench Machine Learning

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

Conditional Expectation Propagation

no code implementations27 Oct 2019 Zheng Wang, Shandian Zhe

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

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 +2

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 #18 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 #20 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

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 +2

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.

Clustering Denoising +1

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 +1

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 slot-filling +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.

BIG-bench Machine Learning

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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