Search Results for author: Fei-Yue Wang

Found 46 papers, 13 papers with code

TemPrompt: Multi-Task Prompt Learning for Temporal Relation Extraction in RAG-based Crowdsourcing Systems

no code implementations21 Jun 2024 Jing Yang, Yu Zhao, Linyao Yang, Xiao Wang, Long Chen, Fei-Yue Wang

Temporal relation extraction (TRE) aims to grasp the evolution of events or actions, and thus shape the workflow of associated tasks, so it holds promise in helping understand task requests initiated by requesters in crowdsourcing systems.

Contrastive Learning Language Modelling +4

RAG-based Crowdsourcing Task Decomposition via Masked Contrastive Learning with Prompts

no code implementations4 Jun 2024 Jing Yang, Xiao Wang, Yu Zhao, Yuhang Liu, Fei-Yue Wang

Therefore, we present a Prompt-Based Contrastive learning framework for TD (PBCT), which incorporates a prompt-based trigger detector to overcome dependence.

Common Sense Reasoning Contrastive Learning +3

3D Unsupervised Learning by Distilling 2D Open-Vocabulary Segmentation Models for Autonomous Driving

1 code implementation24 May 2024 Boyi Sun, Yuhang Liu, Xingxia Wang, Bin Tian, Long Chen, Fei-Yue Wang

We achieved a record-breaking 47. 73% mIoU on the annotation-free point cloud segmentation task in nuScenes, surpassing the previous best model by 10. 70% mIoU.

Autonomous Driving Knowledge Distillation +1

AMCEN: An Attention Masking-based Contrastive Event Network for Two-stage Temporal Knowledge Graph Reasoning

no code implementations16 May 2024 Jing Yang, Xiao Wang, Yutong Wang, Jiawei Wang, Fei-Yue Wang

To achieve more accurate TKG reasoning, we propose an attention masking-based contrastive event network (AMCEN) with local-global temporal patterns for the two-stage prediction of future events.

Contrastive Learning Knowledge Graphs +1

RIME: Robust Preference-based Reinforcement Learning with Noisy Preferences

1 code implementation27 Feb 2024 Jie Cheng, Gang Xiong, Xingyuan Dai, Qinghai Miao, Yisheng Lv, Fei-Yue Wang

Our experiments on robotic manipulation and locomotion tasks demonstrate that RIME significantly enhances the robustness of the state-of-the-art PbRL method.


Conversational Crowdsensing: A Parallel Intelligence Powered Novel Sensing Approach

no code implementations4 Feb 2024 Zhengqiu Zhu, Yong Zhao, Bin Chen, Sihang Qiu, Kai Xu, Quanjun Yin, Jincai Huang, Zhong Liu, Fei-Yue Wang

The transition from CPS-based Industry 4. 0 to CPSS-based Industry 5. 0 brings new requirements and opportunities to current sensing approaches, especially in light of recent progress in Chatbots and Large Language Models (LLMs).


Evolutionary City: Towards a Flexible, Agile and Symbiotic System

no code implementations6 Nov 2023 Xi Chen, Wei Hu, Jingru Yu, Ding Wang, Shengyue Yao, Yilun Lin, Fei-Yue Wang

This paper introduces a novel approach, aiming to enable cities to evolve and respond more effectively to such dynamic demand.

Decision Making Management

Enhancing Traffic Object Detection in Variable Illumination with RGB-Event Fusion

no code implementations1 Nov 2023 Zhanwen Liu, Nan Yang, Yang Wang, Yuke Li, Xiangmo Zhao, Fei-Yue Wang

To address this issue, we introduce bio-inspired event cameras and propose a novel Structure-aware Fusion Network (SFNet) that extracts sharp and complete object structures from the event stream to compensate for the lost information in images through cross-modality fusion, enabling the network to obtain illumination-robust representations for traffic object detection.

Object object-detection +2

HPL-ViT: A Unified Perception Framework for Heterogeneous Parallel LiDARs in V2V

no code implementations27 Sep 2023 Yuhang Liu, Boyi Sun, Yuke Li, Yuzheng Hu, Fei-Yue Wang

It uses a graph-attention Transformer to extract domain-specific features for each agent, coupled with a cross-attention mechanism for the final fusion.

Autonomous Driving Diversity +1

Towards Integrated Traffic Control with Operating Decentralized Autonomous Organization

no code implementations25 Jul 2023 Shengyue Yao, Jingru Yu, Yi Yu, Jia Xu, Xingyuan Dai, Honghai Li, Fei-Yue Wang, Yilun Lin

Furthermore, an operation algorithm is proposed regarding the issue of structural rigidity in DAO.

IR Design for Application-Specific Natural Language: A Case Study on Traffic Data

no code implementations13 Jul 2023 Wei Hu, Xuhong Wang, Ding Wang, Shengyue Yao, Zuqiu Mao, Li Li, Fei-Yue Wang, Yilun Lin

In the realm of software applications in the transportation industry, Domain-Specific Languages (DSLs) have enjoyed widespread adoption due to their ease of use and various other benefits.

Milestones in Autonomous Driving and Intelligent Vehicles Part II: Perception and Planning

no code implementations3 Jun 2023 Long Chen, Siyu Teng, Bai Li, Xiaoxiang Na, Yuchen Li, Zixuan Li, Jinjun Wang, Dongpu Cao, Nanning Zheng, Fei-Yue Wang

Growing interest in autonomous driving (AD) and intelligent vehicles (IVs) is fueled by their promise for enhanced safety, efficiency, and economic benefits.

Autonomous Driving Ethics

TransWorldNG: Traffic Simulation via Foundation Model

1 code implementation25 May 2023 Ding Wang, Xuhong Wang, Liang Chen, Shengyue Yao, Ming Jing, Honghai Li, Li Li, Shiqiang Bao, Fei-Yue Wang, Yilun Lin

To the best of our knowledge, this is the first traffic simulator that can automatically learn traffic patterns from real-world data and efficiently generate accurate and realistic traffic environments.

Decision Making Management

Milestones in Autonomous Driving and Intelligent Vehicles Part I: Control, Computing System Design, Communication, HD Map, Testing, and Human Behaviors

no code implementations12 May 2023 Long Chen, Yuchen Li, Chao Huang, Yang Xing, Daxin Tian, Li Li, Zhongxu Hu, Siyu Teng, Chen Lv, Jinjun Wang, Dongpu Cao, Nanning Zheng, Fei-Yue Wang

Our work is divided into 3 independent articles and the first part is a Survey of Surveys (SoS) for total technologies of AD and IVs that involves the history, summarizes the milestones, and provides the perspectives, ethics, and future research directions.

Autonomous Driving Ethics

Milestones in Autonomous Driving and Intelligent Vehicles: Survey of Surveys

no code implementations30 Mar 2023 Long Chen, Yuchen Li, Chao Huang, Bai Li, Yang Xing, Daxin Tian, Li Li, Zhongxu Hu, Xiaoxiang Na, Zixuan Li, Siyu Teng, Chen Lv, Jinjun Wang, Dongpu Cao, Nanning Zheng, Fei-Yue Wang

Interest in autonomous driving (AD) and intelligent vehicles (IVs) is growing at a rapid pace due to the convenience, safety, and economic benefits.

Autonomous Driving Ethics

Conservative-Progressive Collaborative Learning for Semi-supervised Semantic Segmentation

1 code implementation30 Nov 2022 Siqi Fan, Fenghua Zhu, Zunlei Feng, Yisheng Lv, Mingli Song, Fei-Yue Wang

Pseudo supervision is regarded as the core idea in semi-supervised learning for semantic segmentation, and there is always a tradeoff between utilizing only the high-quality pseudo labels and leveraging all the pseudo labels.

Segmentation Semi-Supervised Semantic Segmentation

GraphFit: Learning Multi-scale Graph-Convolutional Representation for Point Cloud Normal Estimation

1 code implementation23 Jul 2022 Keqiang Li, Mingyang Zhao, Huaiyu Wu, Dong-Ming Yan, Zhen Shen, Fei-Yue Wang, Gang Xiong

We propose a precise and efficient normal estimation method that can deal with noise and nonuniform density for unstructured 3D point clouds.

Surface Normals Estimation

Deep Rank-Consistent Pyramid Model for Enhanced Crowd Counting

2 code implementations13 Jan 2022 Jiaqi Gao, Zhizhong Huang, Yiming Lei, Hongming Shan, James Z. Wang, Fei-Yue Wang, Junping Zhang

Specifically, we propose a Deep Rank-consistEnt pyrAmid Model (DREAM), which makes full use of rank consistency across coarse-to-fine pyramid features in latent spaces for enhanced crowd counting with massive unlabeled images.

Crowd Counting

Two Heads are Better Than One: Hypergraph-Enhanced Graph Reasoning for Visual Event Ratiocination

no code implementations International Conference on Machine Learning 2021 Wenbo Zheng, Lan Yan, Chao Gou, Fei-Yue Wang

Even with a still image, humans can ratiocinate various visual cause-and-effect descriptions before, at present, and after, as well as beyond the given image.

 Ranked #1 on Visual Storytelling on VIST (using extra training data)

Visual Storytelling

SCF-Net: Learning Spatial Contextual Features for Large-Scale Point Cloud Segmentation

1 code implementation CVPR 2021 Siqi Fan, Qiulei Dong, Fenghua Zhu, Yisheng Lv, Peijun Ye, Fei-Yue Wang

For each 3D point, the local polar representation block is firstly explored to construct a spatial representation that is invariant to the z-axis rotation, then the dual-distance attentive pooling block is designed to utilize the representations of its neighbors for learning more discriminative local features according to both the geometric and feature distances among them, and finally, the global contextual feature block is designed to learn a global context for each 3D point by utilizing its spatial location and the volume ratio of the neighborhood to the global point cloud.

3D Semantic Segmentation Decoder +2

Drill the Cork of Information Bottleneck by Inputting the Most Important Data

no code implementations15 May 2021 Xinyu Peng, Jiawei Zhang, Fei-Yue Wang, Li Li

As a promising tool to better understand the learning dynamic of minibatch SGD, the information bottleneck (IB) theory claims that the optimization process consists of an initial fitting phase and the following compression phase.

Deep Q Learning from Dynamic Demonstration with Behavioral Cloning

no code implementations1 Jan 2021 Xiaoshuang Li, Junchen Jin, Xiao Wang, Fei-Yue Wang

This study proposes a novel approach integrating deep Q learning from dynamic demonstrations with a behavioral cloning model (DQfDD-BC), which includes a supervised learning technique of instructing a DRL model to enhance its performance.

OpenAI Gym Q-Learning

FCM-RDpA: TSK Fuzzy Regression Model Construction Using Fuzzy C-Means Clustering, Regularization, DropRule, and Powerball AdaBelief

2 code implementations30 Nov 2020 Zhenhua Shi, Dongrui Wu, Chenfeng Guo, Changming Zhao, Yuqi Cui, Fei-Yue Wang

To effectively optimize Takagi-Sugeno-Kang (TSK) fuzzy systems for regression problems, a mini-batch gradient descent with regularization, DropRule, and AdaBound (MBGD-RDA) algorithm was recently proposed.

Clustering regression

Dynamic Fusion based Federated Learning for COVID-19 Detection

no code implementations22 Sep 2020 Weishan Zhang, Tao Zhou, Qinghua Lu, Xiao Wang, Chunsheng Zhu, Haoyun Sun, Zhipeng Wang, Sin Kit Lo, Fei-Yue Wang

To improve communication efficiency and model performance, in this paper, we propose a novel dynamic fusion-based federated learning approach for medical diagnostic image analysis to detect COVID-19 infections.

BIG-bench Machine Learning Decision Making +3

Conditional Uncorrelation and Efficient Non-approximate Subset Selection in Sparse Regression

no code implementations8 Sep 2020 Jianji Wang, Qi Liu, Shupei Zhang, Nanning Zheng, Fei-Yue Wang

By the proposed method, the computational complexity is reduced from $O(\frac{1}{6}{k^3}+mk^2+mkd)$ to $O(\frac{1}{6}{k^3}+\frac{1}{2}mk^2)$ for each candidate subset in sparse regression.


Convolutional Ordinal Regression Forest for Image Ordinal Estimation

no code implementations7 Aug 2020 Haiping Zhu, Hongming Shan, Yuheng Zhang, Lingfu Che, Xiaoyang Xu, Junping Zhang, Jianbo Shi, Fei-Yue Wang

We propose a novel ordinal regression approach, termed Convolutional Ordinal Regression Forest or CORF, for image ordinal estimation, which can integrate ordinal regression and differentiable decision trees with a convolutional neural network for obtaining precise and stable global ordinal relationships.

Age Estimation Binary Classification +1

Defining Digital Quadruplets in the Cyber-Physical-Social Space for Parallel Driving

no code implementations26 Jul 2020 Teng Liu, Yang Xing, Long Chen, Dongpu Cao, Fei-Yue Wang

The objectives of the three virtual digital vehicles are interacting, guiding, simulating and improving with the real vehicles.


Digital Quadruplets for Cyber-Physical-Social Systems based Parallel Driving: From Concept to Applications

no code implementations21 Jul 2020 Teng Liu, Xing Yang, Hong Wang, Xiaolin Tang, Long Chen, Huilong Yu, Fei-Yue Wang

The three virtual vehicles (descriptive, predictive, and prescriptive) dynamically interact with the real one in order to enhance the safety and performance of the real vehicle.


Adaptive and Azimuth-Aware Fusion Network of Multimodal Local Features for 3D Object Detection

no code implementations10 Oct 2019 Yonglin Tian, Kunfeng Wang, Yuang Wang, Yulin Tian, Zilei Wang, Fei-Yue Wang

We adopt different modalities of LiDAR data to generate richer features and present an adaptive and azimuth-aware network to aggregate local features from image, bird's eye view maps and point cloud.

3D Object Detection object-detection +1

A Heuristic Algorithm for the Fabric Spreading and Cutting Problem in Apparel Factories

no code implementations13 Mar 2019 Xiuqin Shang, Dayong Shen, Fei-Yue Wang, Timo R. Nyberg

Firstly the constructive procedure creates a set of lays in sequence, and then the improving loop tries to pick each lay from the lay set and rearrange the remaining lays into a smaller lay set.

Parallel Medical Imaging for Intelligent Medical Image Analysis: Concepts, Methods, and Applications

no code implementations12 Mar 2019 Chao Gou, Tianyu Shen, Wenbo Zheng, Huadan Xue, Hui Yu, Qiang Ji, Zhengyu Jin, Fei-Yue Wang

Artificial imaging systems are introduced to select and prescriptively generate medical image data in a knowledge-driven way to utilize medical domain knowledge.

Accelerating Minibatch Stochastic Gradient Descent using Typicality Sampling

no code implementations11 Mar 2019 Xinyu Peng, Li Li, Fei-Yue Wang

Machine learning, especially deep neural networks, has been rapidly developed in fields including computer vision, speech recognition and reinforcement learning.

Reinforcement Learning (RL) speech-recognition +2

Mutual Clustering on Comparative Texts via Heterogeneous Information Networks

no code implementations9 Mar 2019 Jianping Cao, Senzhang Wang, Danyan Wen, Zhaohui Peng, Philip S. Yu, Fei-Yue Wang

HINT first models multi-sourced texts (e. g. news and tweets) as heterogeneous information networks by introducing the shared ``anchor texts'' to connect the comparative texts.

Clustering Text Clustering +1

An Efficient Deep Reinforcement Learning Model for Urban Traffic Control

1 code implementation6 Aug 2018 Yilun Lin, Xingyuan Dai, Li Li, Fei-Yue Wang

Urban Traffic Control (UTC) plays an essential role in Intelligent Transportation System (ITS) but remains difficult.

reinforcement-learning Reinforcement Learning (RL)

M4CD: A Robust Change Detection Method for Intelligent Visual Surveillance

no code implementations14 Feb 2018 Kunfeng Wang, Chao Gou, Fei-Yue Wang

Secondly, multiple heterogeneous features (including brightness variation, chromaticity variation, and texture variation) are extracted by comparing the input frame with the background model, and a multi-source learning strategy is designed to online estimate the probability distributions for both foreground and background.

Change Detection

Scene-Specific Pedestrian Detection Based on Parallel Vision

1 code implementation23 Dec 2017 Wenwen Zhang, Kunfeng Wang, Hua Qu, Jihong Zhao, Fei-Yue Wang

In order to make the generic scene pedestrian detectors work well in specific scenes, the labeled data from specific scenes are needed to adapt the models to the specific scenes.

object-detection Object Detection +1

The ParallelEye Dataset: Constructing Large-Scale Artificial Scenes for Traffic Vision Research

no code implementations22 Dec 2017 Xuan Li, Kunfeng Wang, Yonglin Tian, Lan Yan, Fei-Yue Wang

As a result, we present a viable implementation pipeline for constructing large-scale artificial scenes for traffic vision research.

Instance Segmentation Object Tracking +2

Training and Testing Object Detectors with Virtual Images

no code implementations22 Dec 2017 Yonglin Tian, Xuan Li, Kunfeng Wang, Fei-Yue Wang

In the area of computer vision, deep learning has produced a variety of state-of-the-art models that rely on massive labeled data.


DeepTrend: A Deep Hierarchical Neural Network for Traffic Flow Prediction

no code implementations11 Jul 2017 Xingyuan Dai, Rui Fu, Yilun Lin, Li Li, Fei-Yue Wang

Detrending based methods decompose original flow series into trend and residual series, in which trend describes the fixed temporal pattern in traffic flow and residual series is used for prediction.

Time Series Time Series Analysis

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