4 citations · 6 across the 17 of their papers we have counts for
19 papers
Why Do VLMs Fail at Remote Physiological Measurement? Rethinking with Physiological Grounding and Numerical Alignment
Xiao Yang, Zekun Zhang, Yuxuan Fan +5
Video-based remote physiological measurement (RPM) has broad applications, while Vision-Language Models (VLMs) provide a promising opportunity to enable end-to-end physiological mo…
MILD: Mediator Agent System with Bidirectional Perception and Multi-Layered Alignment for Human-Vehicle Collaboration
Jiyao Wang, Yunbiao Wang, Yubo Jiao +6
Prior studies report that partial driving automation can increase the cognitive demands on human drivers. This effect largely arises from human drivers' lack of transparent insight…
From Awareness to Intent: Mitigating Silent Driving System Failures through Prospective Situation Awareness Enhancing Interfaces
Jiyao Wang, Song Yan, Xiao Yang +6
Silent automation failures, where a system fails to detect a hazard without warning, pose a critical safety challenge for partially automated vehicles. While research has mostly fo…
FedHUG: Federated Heterogeneous Unsupervised Generalization for Remote Physiological Measurements
Xiao Yang, Dengbo He, Jiyao Wang +2
Remote physiological measurement gained wide attention, while it requires collecting users' privacy-sensitive information, and existing contactless measurements still rely on label…
PhysDrive: A Multimodal Remote Physiological Measurement Dataset for In-vehicle Driver Monitoring
Jiyao Wang, Xiao Yang, Qingyong Hu +6
Robust and unobtrusive in-vehicle physiological monitoring is crucial for ensuring driving safety and user experience. While remote physiological measurement (RPM) offers a promisi…
Not Only Consistency: Enhance Test-Time Adaptation with Spatio-temporal Inconsistency for Remote Physiological Measurement
Xiao Yang, Jiyao Wang, Yuxuan Fan +6
Remote physiological measurement (RPM) has emerged as a promising non-invasive method for monitoring physiological signals using the non-contact device. Although various domain ada…
The impact of the following vehicles behaviors on the car following behaviors of the ego-vehicle
Yang Liu, Jiahao Zhang, Yuxuan Ouyang +2
Among all types of crashes, rear-end crashes dominate, which are closely related to the car-following (CF) behaviors. Traditional CF behavior models focused on the influence of the…
Do Electric Vehicles Induce More Motion Sickness Than Fuel Vehicles? A Survey Study in China
Weiyin Xie, Chunxi Huang, Jiyao Wang +1
Electric vehicles (EVs) are a promising alternative to fuel vehicles (FVs), given some unique characteristics of EVs, for example, the low air pollution and maintenance cost. Howev…
Supporting Car-Following Behavior through V2V-Based Beyond-Visual-Range Information Display
Feiqi Gu, Zhixiong Wang, Zhenyu Wang +1
Rear-end collisions constituted a large portion of crashes on the road, despite efforts to mitigate rear-end collisions, such as forward collision warnings. The chance of rear-end…
Align the GAP: Prior-based Unified Multi-Task Remote Physiological Measurement Framework For Domain Generalization and Personalization
Jiyao Wang, Xiao Yang, Hao Lu +2
Multi-source synsemantic domain generalization (MSSDG) for multi-task remote physiological measurement seeks to enhance the generalizability of these metrics and attracts increasin…
Towards Generalizable Drowsiness Monitoring with Physiological Sensors: A Preliminary Study
Jiyao Wang, Suzan Ayas, Jiahao Zhang +3
Accurately detecting drowsiness is vital to driving safety. Among all measures, physiological-signal-based drowsiness monitoring can be more privacy-preserving than a camera-based…
When and How to Integrate Multimodal Large Language Models in College Psychotherapy: Perspectives from Multi-stakeholders
Jiyao Wang, Youyu Sheng, Qihang He +4
As mental health issues rise among college students, there is an increasing interest and demand in leveraging Multimodal Language Models (MLLM) to enhance mental support services,…
STAHGNet: Modeling Hybrid-grained Heterogenous Dependency Efficiently for Traffic Prediction
Jiyao Wang, Zehua Peng, Yijia Zhang +2
Traffic flow prediction plays a critical role in the intelligent transportation system, and it is also a challenging task because of the underlying complex Spatio-temporal patterns…
Modeling Battery Electric Vehicle Users' Charging Decisions in Scenarios with Both Time-Related and Distance-Related Anxiety
Jiyao Wang, Wenbo Zhang, Xiao +3
As one of the most promising alternatives to internal combustion engine vehicles, battery electric vehicles (BEVs) have become increasingly prevalent in recent years. However, rang…
Revisiting Interactions of Multiple Driver States in Heterogenous Population and Cognitive Tasks
Jiyao Wang, Ange Wang, Song Yan +2
In real-world driving scenarios, multiple states occur simultaneously due to individual differences and environmental factors, complicating the analysis and estimation of driver st…
Efficient Mixture-of-Expert for Video-based Driver State and Physiological Multi-task Estimation in Conditional Autonomous Driving
Jiyao Wang, Xiao Yang, Zhenyu Wang +4
Road safety remains a critical challenge worldwide, with approximately 1.35 million fatalities annually attributed to traffic accidents, often due to human errors. As we advance to…
The Influence of Task and Group Disparities over Users' Attitudes Toward Using Large Language Models for Psychotherapy
Qihang He, Jiyao Wang, Dengbo He
The population suffering from mental health disorders has kept increasing in recent years. With the advancements in large language models (LLMs) in diverse fields, LLM-based psycho…
PhysMLE: Generalizable and Priors-Inclusive Multi-task Remote Physiological Measurement
Jiyao Wang, Hao Lu, Ange Wang +4
Remote photoplethysmography (rPPG) has been widely applied to measure heart rate from face videos. To increase the generalizability of the algorithms, domain generalization (DG) at…
GPT as Psychologist? Preliminary Evaluations for GPT-4V on Visual Affective Computing
Hao Lu, Xuesong Niu, Jiyao Wang +12
Multimodal large language models (MLLMs) are designed to process and integrate information from multiple sources, such as text, speech, images, and videos. Despite its success in l…