Yanchen Guan
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View article: Eyes on the Road, Mind Beyond Vision: Context-Aware Multi-modal Enhanced Risk Anticipation
Eyes on the Road, Mind Beyond Vision: Context-Aware Multi-modal Enhanced Risk Anticipation Open
View article: Domain-enhanced dual-branch model for efficient and interpretable accident anticipation
Domain-enhanced dual-branch model for efficient and interpretable accident anticipation Open
View article: World model-based end-to-end scene generation for accident anticipation in autonomous driving
World model-based end-to-end scene generation for accident anticipation in autonomous driving Open
Reliable anticipation of traffic accidents is essential for advancing autonomous driving systems. However, this objective is limited by two fundamental challenges: the scarcity of diverse, high-quality training data and the frequent absenc…
View article: Domain-Enhanced Dual-Branch Model for Efficient and Interpretable Accident Anticipation
Domain-Enhanced Dual-Branch Model for Efficient and Interpretable Accident Anticipation Open
Developing precise and computationally efficient traffic accident anticipation system is crucial for contemporary autonomous driving technologies, enabling timely intervention and loss prevention. In this paper, we propose an accident anti…
View article: World Model-Based End-to-End Scene Generation for Accident Anticipation in Autonomous Driving
World Model-Based End-to-End Scene Generation for Accident Anticipation in Autonomous Driving Open
Reliable anticipation of traffic accidents is essential for advancing autonomous driving systems. However, this objective is limited by two fundamental challenges: the scarcity of diverse, high-quality training data and the frequent absenc…
View article: Eyes on the Road, Mind Beyond Vision: Context-Aware Multi-modal Enhanced Risk Anticipation
Eyes on the Road, Mind Beyond Vision: Context-Aware Multi-modal Enhanced Risk Anticipation Open
Accurate accident anticipation remains challenging when driver cognition and dynamic road conditions are underrepresented in predictive models. In this paper, we propose CAMERA (Context-Aware Multi-modal Enhanced Risk Anticipation), a mult…
View article: AMD: Adaptive Momentum and Decoupled Contrastive Learning Framework for Robust Long-Tail Trajectory Prediction
AMD: Adaptive Momentum and Decoupled Contrastive Learning Framework for Robust Long-Tail Trajectory Prediction Open
Accurately predicting the future trajectories of traffic agents is essential in autonomous driving. However, due to the inherent imbalance in trajectory distributions, tail data in natural datasets often represents more complex and hazardo…