Search Results for author: Hong Wang

Found 68 papers, 29 papers with code

Recursive Counterfactual Deconfounding for Object Recognition

no code implementations25 Sep 2023 Jiayin Sun, Hong Wang, Qiulei Dong

Image recognition is a classic and common task in the computer vision field, which has been widely applied in the past decade.

Object Recognition Open Set Learning

Exploring Robust Features for Improving Adversarial Robustness

no code implementations9 Sep 2023 Hong Wang, Yuefan Deng, Shinjae Yoo, Yuewei Lin

In this paper, we strive to explore the robust features which are not affected by the adversarial perturbations, i. e., invariant to the clean image and its adversarial examples, to improve the model's adversarial robustness.

Adversarial Robustness Disentanglement

Evolving Testing Scenario Generation Method and Intelligence Evaluation Framework for Automated Vehicles

no code implementations12 Jun 2023 Yining Ma, Wei Jiang, Lingtong Zhang, Junyi Chen, Hong Wang, Chen Lv, Xuesong Wang, Lu Xiong

Current testing scenarios typically employ predefined or scripted BVs, which inadequately reflect the complexity of human-like social behaviors in real-world driving scenarios, and also lack a systematic metric for evaluating the comprehensive intelligence of AVs.

STEPS: A Benchmark for Order Reasoning in Sequential Tasks

no code implementations7 Jun 2023 Weizhi Wang, Hong Wang, Xifeng Yan

Therefore, to verify the order reasoning capability of current neural models in sequential tasks, we propose a challenging benchmark , named STEPS.

Cross-Modal Vertical Federated Learning for MRI Reconstruction

no code implementations5 Jun 2023 Yunlu Yan, Hong Wang, Yawen Huang, Nanjun He, Lei Zhu, Yuexiang Li, Yong Xu, Yefeng Zheng

To this end, we formulate this practical-yet-challenging cross-modal vertical federated learning task, in which shape data from multiple hospitals have different modalities with a small amount of multi-modality data collected from the same individuals.

Disentanglement Federated Learning +1

Predicting Token Impact Towards Efficient Vision Transformer

no code implementations24 May 2023 Hong Wang, Su Yang, Xiaoke Huang, Weishan Zhang

Token filtering to reduce irrelevant tokens prior to self-attention is a straightforward way to enable efficient vision Transformer.

feature selection

Self-Aware Trajectory Prediction for Safe Autonomous Driving

no code implementations16 May 2023 Wenbo Shao, Jun Li, Hong Wang

Trajectory prediction is one of the key components of the autonomous driving software stack.

Autonomous Driving Trajectory Prediction

Bot or Human? Detecting ChatGPT Imposters with A Single Question

1 code implementation10 May 2023 Hong Wang, Xuan Luo, Weizhi Wang, Xifeng Yan

Large language models like ChatGPT have recently demonstrated impressive capabilities in natural language understanding and generation, enabling various applications including translation, essay writing, and chit-chatting.

Language Modelling Large Language Model +2

Interactive Segmentation as Gaussian Process Classification

1 code implementation28 Feb 2023 Minghao Zhou, Hong Wang, Qian Zhao, Yuexiang Li, Yawen Huang, Deyu Meng, Yefeng Zheng

Against this issue, in this paper, we propose to formulate the IS task as a Gaussian process (GP)-based pixel-wise binary classification model on each image.

Binary Classification Classification +3

Planning Automated Driving with Accident Experience Referencing and Common-sense Inferencing

no code implementations26 Jan 2023 Shaobo Qiu, Ji Li, Guoxi Chen, Hong Wang, Boqi Li

In this work, we present the concept of an Automated Driving Strategical Brain (ADSB): a framework of a scene perception and scene safety evaluation system that works at a higher abstraction level, incorporating experience referencing, common-sense inferring and goal-and-value judging capabilities, to provide a contextual perspective for decision making within automated driving planning.

Common Sense Reasoning Decision Making

Chaos to Order: A Label Propagation Perspective on Source-Free Domain Adaptation

no code implementations20 Jan 2023 Chunwei Wu, Guitao Cao, Yan Li, Xidong Xi, Wenming Cao, Hong Wang

Inspired by this insight, we present Chaos to Order (CtO), a novel approach for SFDA that strives to constrain semantic credibility and propagate label information among target subpopulations.

Clustering Source-Free Domain Adaptation

How Does Traffic Environment Quantitatively Affect the Autonomous Driving Prediction?

no code implementations11 Jan 2023 Wenbo Shao, Yanchao Xu, Jun Li, Chen Lv, Weida Wang, Hong Wang

The results indicate that the deep ensemble-based method has advantages in improving prediction robustness and estimating epistemic uncertainty.

Autonomous Driving Decision Making +1

SemiCVT: Semi-Supervised Convolutional Vision Transformer for Semantic Segmentation

no code implementations CVPR 2023 Huimin Huang, Shiao Xie, Lanfen Lin, Ruofeng Tong, Yen-Wei Chen, Yuexiang Li, Hong Wang, Yawen Huang, Yefeng Zheng

Semi-supervised learning improves data efficiency of deep models by leveraging unlabeled samples to alleviate the reliance on a large set of labeled samples.

Semantic Segmentation

Interactive Segmentation As Gaussion Process Classification

1 code implementation CVPR 2023 Minghao Zhou, Hong Wang, Qian Zhao, Yuexiang Li, Yawen Huang, Deyu Meng, Yefeng Zheng

Against this issue, in this paper, we propose to formulate the IS task as a Gaussian process (GP)-based pixel-wise binary classification model on each image.

Binary Classification Classification +3

Orientation-Shared Convolution Representation for CT Metal Artifact Learning

1 code implementation26 Dec 2022 Hong Wang, Qi Xie, Yuexiang Li, Yawen Huang, Deyu Meng, Yefeng Zheng

During X-ray computed tomography (CT) scanning, metallic implants carrying with patients often lead to adverse artifacts in the captured CT images and then impair the clinical treatment.

Computed Tomography (CT) Metal Artifact Reduction

No driver, No Regulation? --Online Legal Driving Behavior Monitoring for Self-driving Vehicles

no code implementations8 Dec 2022 Wenhao Yu, Chengxiang Zhao, Jiaxin Liu, Yingkai Yang, Xiaohan Ma, Jun Li, Weida Wang, Hong Wang, Ding Zhao, Xiaosong Hu

To address these challenges, this paper aims to digitize traffic law comprehensively and provide an application for online monitoring of legal driving behavior for autonomous vehicles.

Autonomous Driving Decision Making

Spatial-Temporal Attention Network for Open-Set Fine-Grained Image Recognition

no code implementations25 Nov 2022 Jiayin Sun, Hong Wang, Qiulei Dong

To address this problem, motivated by the temporal attention mechanism in brains, we propose a spatial-temporal attention network for learning fine-grained feature representations, called STAN, where the features learnt by implementing a sequence of spatial self-attention operations corresponding to multiple moments are aggregated progressively.

Fine-Grained Image Recognition Open Set Learning

SOTIF Entropy: Online SOTIF Risk Quantification and Mitigation for Autonomous Driving

1 code implementation8 Nov 2022 Liang Peng, Boqi Li, Wenhao Yu, Kai Yang, Wenbo Shao, Hong Wang

Therefore, this paper proposes the "Self-Surveillance and Self-Adaption System" as a systematic approach to online minimize the SOTIF risk, which aims to provide a systematic solution for monitoring, quantification, and mitigation of inherent and external risks.

Autonomous Driving Decision Making

PeSOTIF: a Challenging Visual Dataset for Perception SOTIF Problems in Long-tail Traffic Scenarios

1 code implementation7 Nov 2022 Liang Peng, Jun Li, Wenbo Shao, Hong Wang

Perception algorithms in autonomous driving systems confront great challenges in long-tail traffic scenarios, where the problems of Safety of the Intended Functionality (SOTIF) could be triggered by the algorithm performance insufficiencies and dynamic operational environment.

Autonomous Driving object-detection +1

Explanations from Large Language Models Make Small Reasoners Better

no code implementations13 Oct 2022 Shiyang Li, Jianshu Chen, Yelong Shen, Zhiyu Chen, Xinlu Zhang, Zekun Li, Hong Wang, Jing Qian, Baolin Peng, Yi Mao, Wenhu Chen, Xifeng Yan

Integrating free-text explanations to in-context learning of large language models (LLM) is shown to elicit strong reasoning capabilities along with reasonable explanations.

Explanation Generation Multi-Task Learning

Towards Theoretically Inspired Neural Initialization Optimization

1 code implementation12 Oct 2022 Yibo Yang, Hong Wang, Haobo Yuan, Zhouchen Lin

With NIO, we improve the classification performance of a variety of neural architectures on CIFAR-10, CIFAR-100, and ImageNet.

Controllable Dialogue Simulation with In-Context Learning

1 code implementation9 Oct 2022 Zekun Li, Wenhu Chen, Shiyang Li, Hong Wang, Jing Qian, Xifeng Yan

Experimental results on the MultiWOZ dataset demonstrate that training a model on the simulated dialogues leads to even better performance than using the same amount of human-generated dialogues under the challenging low-resource settings, with as few as 85 dialogues as a seed.

Data Augmentation Language Modelling +1

KXNet: A Model-Driven Deep Neural Network for Blind Super-Resolution

1 code implementation21 Sep 2022 Jiahong Fu, Hong Wang, Qi Xie, Qian Zhao, Deyu Meng, Zongben Xu

Although current deep learning-based methods have gained promising performance in the blind single image super-resolution (SISR) task, most of them mainly focus on heuristically constructing diverse network architectures and put less emphasis on the explicit embedding of the physical generation mechanism between blur kernels and high-resolution (HR) images.

Blind Super-Resolution Image Super-Resolution +1

CAMO-MOT: Combined Appearance-Motion Optimization for 3D Multi-Object Tracking with Camera-LiDAR Fusion

no code implementations6 Sep 2022 Li Wang, Xinyu Zhang, Wenyuan Qin, Xiaoyu Li, Lei Yang, Zhiwei Li, Lei Zhu, Hong Wang, Jun Li, Huaping Liu

As such, we propose a novel camera-LiDAR fusion 3D MOT framework based on the Combined Appearance-Motion Optimization (CAMO-MOT), which uses both camera and LiDAR data and significantly reduces tracking failures caused by occlusion and false detection.

3D Multi-Object Tracking Autonomous Driving +1

Limitations of Language Models in Arithmetic and Symbolic Induction

no code implementations9 Aug 2022 Jing Qian, Hong Wang, Zekun Li, Shiyang Li, Xifeng Yan

LMs with tutor is able to deliver 100% accuracy in situations of OOD and repeating symbols, shedding new insights on the boundary of large LMs in induction.

Context-Consistent Semantic Image Editing with Style-Preserved Modulation

1 code implementation13 Jul 2022 Wuyang Luo, Su Yang, Hong Wang, Bo Long, Weishan Zhang

Semantic image editing utilizes local semantic label maps to generate the desired content in the edited region.

A Holistic Robust Motion Controller Framework for Autonomous Platooning

no code implementations10 Jun 2022 Hong Wang, Li-Ming Peng, Zi-Chun Wei, Kai Yang, Xian-Xu Bai, Luo Jiang, Ehsan Hashemi

The output from UCL will be delivered to the lower-level motion-planning layer (LML) as reference signals.

Motion Planning

Adaptive Convolutional Dictionary Network for CT Metal Artifact Reduction

1 code implementation16 May 2022 Hong Wang, Yuexiang Li, Deyu Meng, Yefeng Zheng

By unfolding every iterative substep of the proposed algorithm into a network module, we explicitly embed the prior structure into a deep network, \emph{i. e.,} a clear interpretability for the MAR task.

Computed Tomography (CT) Metal Artifact Reduction

Designing thermal radiation metamaterials via hybrid adversarial autoencoder and Bayesian optimization

no code implementations26 Apr 2022 Dezhao Zhu, Jiang Guo, Gang Yu, C. Y. Zhao, Hong Wang, Shenghong Ju

Designing thermal radiation metamaterials is challenging especially for problems with high degrees of freedom and complex objective.

Bayesian Optimization

Low-light Image Enhancement by Retinex Based Algorithm Unrolling and Adjustment

no code implementations12 Feb 2022 Xinyi Liu, Qi Xie, Qian Zhao, Hong Wang, Deyu Meng

Besides, to avoid manually parameter tuning, we also propose a self-supervised fine-tuning strategy, which can always guarantee a promising performance.

Low-Light Image Enhancement Rolling Shutter Correction

InDuDoNet+: A Deep Unfolding Dual Domain Network for Metal Artifact Reduction in CT Images

1 code implementation23 Dec 2021 Hong Wang, Yuexiang Li, Haimiao Zhang, Deyu Meng, Yefeng Zheng

To alleviate these issues, in the paper, we construct a novel deep unfolding dual domain network, termed InDuDoNet+, into which CT imaging process is finely embedded.

Computed Tomography (CT) Metal Artifact Reduction

InDuDoNet: An Interpretable Dual Domain Network for CT Metal Artifact Reduction

1 code implementation11 Sep 2021 Hong Wang, Yuexiang Li, Haimiao Zhang, Jiawei Chen, Kai Ma, Deyu Meng, Yefeng Zheng

For the task of metal artifact reduction (MAR), although deep learning (DL)-based methods have achieved promising performances, most of them suffer from two problems: 1) the CT imaging geometry constraint is not fully embedded into the network during training, leaving room for further performance improvement; 2) the model interpretability is lack of sufficient consideration.

Metal Artifact Reduction

AGKD-BML: Defense Against Adversarial Attack by Attention Guided Knowledge Distillation and Bi-directional Metric Learning

1 code implementation ICCV 2021 Hong Wang, Yuefan Deng, Shinjae Yoo, Haibin Ling, Yuewei Lin

The attention knowledge is obtained from a weight-fixed model trained on a clean dataset, referred to as a teacher model, and transferred to a model that is under training on adversarial examples (AEs), referred to as a student model.

Adversarial Attack Adversarial Robustness +2

RCDNet: An Interpretable Rain Convolutional Dictionary Network for Single Image Deraining

1 code implementation14 Jul 2021 Hong Wang, Qi Xie, Qian Zhao, Yuexiang Li, Yong Liang, Yefeng Zheng, Deyu Meng

To handle such an ill-posed single image deraining task, in this paper, we specifically build a novel deep architecture, called rain convolutional dictionary network (RCDNet), which embeds the intrinsic priors of rain streaks and has clear interpretability.

Single Image Deraining

Symmetric Reduction of Regular Controlled Lagrangian System with Momentum Map

no code implementations11 Mar 2021 Hong Wang

Then we give a good expression of the dynamical vector field of the RCL system, such that we can describe the RCL-equivalence for the RCL systems.

Symplectic Geometry Differential Geometry Dynamical Systems 53D20, 70H33, 70Q05

From Rain Generation to Rain Removal

1 code implementation CVPR 2021 Hong Wang, Zongsheng Yue, Qi Xie, Qian Zhao, Yefeng Zheng, Deyu Meng

For the single image rain removal (SIRR) task, the performance of deep learning (DL)-based methods is mainly affected by the designed deraining models and training datasets.

Single Image Deraining Variational Inference

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.


Dueling Deep Q Network for Highway Decision Making in Autonomous Vehicles: A Case Study

no code implementations16 Jul 2020 Teng Liu, Xingyu Mu, Xiaolin Tang, Bing Huang, Hong Wang, Dongpu Cao

This work optimizes the highway decision making strategy of autonomous vehicles by using deep reinforcement learning (DRL).

Autonomous Vehicles Decision Making +2

Transferred Energy Management Strategies for Hybrid Electric Vehicles Based on Driving Conditions Recognition

no code implementations16 Jul 2020 Teng Liu, Xiaolin Tang, Jiaxin Chen, Hong Wang, Wenhao Tan, Yalian Yang

Energy management strategies (EMSs) are the most significant components in hybrid electric vehicles (HEVs) because they decide the potential of energy conservation and emission reduction.

energy management Management +2

Structural Residual Learning for Single Image Rain Removal

no code implementations19 May 2020 Hong Wang, Yichen Wu, Qi Xie, Qian Zhao, Yong Liang, Deyu Meng

Such a structural residual setting guarantees the rain layer extracted by the network finely comply with the prior knowledge of general rain streaks, and thus regulates sound rain shapes capable of being well extracted from rainy images in both training and predicting stages.

Rain Removal

A Model-driven Deep Neural Network for Single Image Rain Removal

1 code implementation CVPR 2020 Hong Wang, Qi Xie, Qian Zhao, Deyu Meng

Specifically, based on the convolutional dictionary learning mechanism for representing rain, we propose a novel single image deraining model and utilize the proximal gradient descent technique to design an iterative algorithm only containing simple operators for solving the model.

Dictionary Learning Single Image Deraining

Knowledge Federation: A Unified and Hierarchical Privacy-Preserving AI Framework

no code implementations5 Feb 2020 Hongyu Li, Dan Meng, Hong Wang, Xiaolin Li

With strict protections and regulations of data privacy and security, conventional machine learning based on centralized datasets is confronted with significant challenges, making artificial intelligence (AI) impractical in many mission-critical and data-sensitive scenarios, such as finance, government, and health.

Federated Learning Privacy Preserving

Optimal Analysis of Subset-Selection Based L_p Low-Rank Approximation

no code implementations NeurIPS 2019 Chen Dan, Hong Wang, Hongyang Zhang, Yuchen Zhou, Pradeep K. Ravikumar

We show that this algorithm has an approximation ratio of $O((k+1)^{1/p})$ for $1\le p\le 2$ and $O((k+1)^{1-1/p})$ for $p\ge 2$.

Optimal Analysis of Subset-Selection Based L_p Low Rank Approximation

no code implementations30 Oct 2019 Chen Dan, Hong Wang, Hongyang Zhang, Yuchen Zhou, Pradeep Ravikumar

We show that this algorithm has an approximation ratio of $O((k+1)^{1/p})$ for $1\le p\le 2$ and $O((k+1)^{1-1/p})$ for $p\ge 2$.

Fine-tune Bert for DocRED with Two-step Process

1 code implementation26 Sep 2019 Hong Wang, Christfried Focke, Rob Sylvester, Nilesh Mishra, William Wang

Modelling relations between multiple entities has attracted increasing attention recently, and a new dataset called DocRED has been collected in order to accelerate the research on the document-level relation extraction.

Document-level Relation Extraction Vocal Bursts Valence Prediction

A Survey on Rain Removal from Video and Single Image

1 code implementation18 Sep 2019 Hong Wang, Yichen Wu, Minghan Li, Qian Zhao, Deyu Meng

The investigations on rain removal from video or a single image has thus been attracting much research attention in the field of computer vision and pattern recognition, and various methods have been proposed against this task in the recent years.

Rain Removal

Simple yet Effective Bridge Reasoning for Open-Domain Multi-Hop Question Answering

no code implementations WS 2019 Wenhan Xiong, Mo Yu, Xiaoxiao Guo, Hong Wang, Shiyu Chang, Murray Campbell, William Yang Wang

To resolve this issue, we introduce a new sub-problem of open-domain multi-hop QA, which aims to recognize the bridge (\emph{i. e.}, the anchor that links to the answer passage) from the context of a set of start passages with a reading comprehension model.

Information Retrieval Multi-hop Question Answering +3

TabFact: A Large-scale Dataset for Table-based Fact Verification

1 code implementation ICLR 2020 Wenhu Chen, Hongmin Wang, Jianshu Chen, Yunkai Zhang, Hong Wang, Shiyang Li, Xiyou Zhou, William Yang Wang

To this end, we construct a large-scale dataset called TabFact with 16k Wikipedia tables as the evidence for 118k human-annotated natural language statements, which are labeled as either ENTAILED or REFUTED.

Fact Checking Fact Verification +3

Inverse Structural Design of Graphene/Boron Nitride Hybrids by Regressional GAN

1 code implementation21 Aug 2019 Yuan Dong, Dawei Li, Chi Zhang, Chuhan Wu, Hong Wang, Ming Xin, Jianlin Cheng, Jian Lin

A significant novelty of the proposed RGAN is that it combines the supervised and regressional convolutional neural network (CNN) with the traditional unsupervised GAN, thus overcoming the common technical barrier in the traditional GANs, which cannot generate data associated with given continuous quantitative labels.

Computational Physics Materials Science Applied Physics

Meta Reasoning over Knowledge Graphs

no code implementations13 Aug 2019 Hong Wang, Wenhan Xiong, Mo Yu, Xiaoxiao Guo, Shiyu Chang, William Yang Wang

The ability to reason over learned knowledge is an innate ability for humans and humans can easily master new reasoning rules with only a few demonstrations.

Few-Shot Learning Knowledge Base Completion +1

TWEETQA: A Social Media Focused Question Answering Dataset

no code implementations ACL 2019 Wenhan Xiong, Jiawei Wu, Hong Wang, Vivek Kulkarni, Mo Yu, Shiyu Chang, Xiaoxiao Guo, William Yang Wang

With social media becoming increasingly pop-ular on which lots of news and real-time eventsare reported, developing automated questionanswering systems is critical to the effective-ness of many applications that rely on real-time knowledge.

Question Answering

Improving Branch Prediction By Modeling Global History with Convolutional Neural Networks

no code implementations20 Jun 2019 Stephen J Tarsa, Chit-Kwan Lin, Gokce Keskin, Gautham Chinya, Hong Wang

CPU branch prediction has hit a wall--existing techniques achieve near-perfect accuracy on 99% of static branches, and yet the mispredictions that remain hide major performance gains.

Self-Supervised Learning for Contextualized Extractive Summarization

2 code implementations ACL 2019 Hong Wang, Xin Wang, Wenhan Xiong, Mo Yu, Xiaoxiao Guo, Shiyu Chang, William Yang Wang

Existing models for extractive summarization are usually trained from scratch with a cross-entropy loss, which does not explicitly capture the global context at the document level.

Extractive Summarization Self-Supervised Learning

Sentence Embedding Alignment for Lifelong Relation Extraction

2 code implementations NAACL 2019 Hong Wang, Wenhan Xiong, Mo Yu, Xiaoxiao Guo, Shiyu Chang, William Yang Wang

We formulate such a challenging problem as lifelong relation extraction and investigate memory-efficient incremental learning methods without catastrophically forgetting knowledge learned from previous tasks.

Incremental Learning Relation Extraction +2

Adversarial Structured Prediction for Multivariate Measures

no code implementations20 Dec 2017 Hong Wang, Ashkan Rezaei, Brian D. Ziebart

Many predicted structured objects (e. g., sequences, matchings, trees) are evaluated using the F-score, alignment error rate (AER), or other multivariate performance measures.

named-entity-recognition Named Entity Recognition +3

Arbitrary-Oriented Scene Text Detection via Rotation Proposals

4 code implementations3 Mar 2017 Jianqi Ma, Weiyuan Shao, Hao Ye, Li Wang, Hong Wang, Yingbin Zheng, xiangyang xue

This paper introduces a novel rotation-based framework for arbitrary-oriented text detection in natural scene images.

Region Proposal Scene Text Detection +1

Adversarial Prediction Games for Multivariate Losses

no code implementations NeurIPS 2015 Hong Wang, Wei Xing, Kaiser Asif, Brian Ziebart

Multivariate loss functions are used to assess performance in many modern prediction tasks, including information retrieval and ranking applications.

Information Retrieval Retrieval

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