31 citations · 58 across the 21 of their papers we have counts for
21 papers
4D-WAM: 4D Consistent World Modeling for Autonomous Driving
Jiacheng Fu, Yibo Yuan, Meng Tian +8
Emerging World-Action Models (WAMs) have demonstrated promising performance in autonomous driving by jointly modeling future driving scene evolution and trajectory planning. Howeve…
SUV: Future Scene Understanding as Video Generation for End-to-End Driving
Yibo Yuan, Jiacheng Fu, Jiangtong Zhu +8
End-to-end driving requires a coherent understanding of future scenes, yet existing methods model these scenes using task-specific heads and output formats, with limited scalabilit…
MetaDAT: Generalizable Trajectory Prediction via Meta Pre-training and Data-Adaptive Test-Time Updating
Yuning Wang, Pu Zhang, Yuan He +2
Existing trajectory prediction methods exhibit significant performance degradation under distribution shifts during test time. Although test-time training techniques have been expl…
Prism: Efficient Test-Time Scaling via Hierarchical Search and Self-Verification for Discrete Diffusion Language Models
Jinbin Bai, Yixuan Li, Yuchen Zhu +8
Inference-time compute has re-emerged as a practical way to improve LLM reasoning. Most test-time scaling (TTS) algorithms rely on autoregressive decoding, which is ill-suited to d…
A Human-Oriented Cooperative Driving Approach: Integrating Driving Intention, State, and Conflict
Qin Wang, Shanmin Pang, Jianwu Fang +4
Human-vehicle cooperative driving serves as a vital bridge to fully autonomous driving by improving driving flexibility and gradually building driver trust and acceptance of autono…
COVLM-RL: Critical Object-Oriented Reasoning for Autonomous Driving Using VLM-Guided Reinforcement Learning
Lin Li, Yuxin Cai, Jianwu Fang +2
End-to-end autonomous driving frameworks face persistent challenges in generalization, training efficiency, and interpretability. While recent methods leverage Vision-Language Mode…
EQ-TAA: Equivariant Traffic Accident Anticipation via Diffusion-Based Accident Video Synthesis
Jianwu Fang, Lei-Lei Li, Zhedong Zheng +4
Traffic Accident Anticipation (TAA) in traffic scenes is a challenging problem for achieving zero fatalities in the future. Current approaches typically treat TAA as a supervised l…
IC-Mapper: Instance-Centric Spatio-Temporal Modeling for Online Vectorized Map Construction
Jiangtong Zhu, Zhao Yang, Yinan Shi +2
Online vector map construction based on visual data can bypass the processes of data collection, post-processing, and manual annotation required by traditional map construction, wh…
HeightMapNet: Explicit Height Modeling for End-to-End HD Map Learning
Wenzhao Qiu, Shanmin Pang, Hao zhang +2
Recent advances in high-definition (HD) map construction from surround-view images have highlighted their cost-effectiveness in deployment. However, prevailing techniques often fal…
Gating Syn-to-Real Knowledge for Pedestrian Crossing Prediction in Safe Driving
Jie Bai, Jianwu Fang, Yisheng Lv +3
Pedestrian Crossing Prediction (PCP) in driving scenes plays a critical role in ensuring the safe operation of intelligent vehicles. Due to the limited observations of pedestrian c…
Abductive Ego-View Accident Video Understanding for Safe Driving Perception
Jianwu Fang, Lei-lei Li, Junfei Zhou +5
We present MM-AU, a novel dataset for Multi-Modal Accident video Understanding. MM-AU contains 11,727 in-the-wild ego-view accident videos, each with temporally aligned text descri…
Vehicle Behavior Prediction by Episodic-Memory Implanted NDT
Peining Shen, Jianwu Fang, Hongkai Yu +1
In autonomous driving, predicting the behavior (turning left, stopping, etc.) of target vehicles is crucial for the self-driving vehicle to make safe decisions and avoid accidents.…
Vision-Based Traffic Accident Detection and Anticipation: A Survey
Jianwu Fang, iahuan Qiao, Jianru Xue +1
Traffic accident detection and anticipation is an obstinate road safety problem and painstaking efforts have been devoted. With the rapid growth of video data, Vision-based Traffic…
Gated Driver Attention Predictor
Tianci Zhao, Xue Bai, Jianwu Fang +1
Driver attention prediction implies the intention understanding of where the driver intends to go and what object the driver concerned about, which commonly provides a driving task…
Enhancing Mapless Trajectory Prediction through Knowledge Distillation
Yuning Wang, Pu Zhang, Lei Bai +1
Scene information plays a crucial role in trajectory forecasting systems for autonomous driving by providing semantic clues and constraints on potential future paths of traffic age…
Learning Residual Model of Model Predictive Control via Random Forests for Autonomous Driving
Kang Zhao, Jianru Xue, Xiangning Meng +2
One major issue in learning-based model predictive control (MPC) for autonomous driving is the contradiction between the system model's prediction accuracy and computation efficien…
UAV Obstacle Avoidance by Human-in-the-Loop Reinforcement in Arbitrary 3D Environment
Xuyang Li, Jianwu Fang, Kai Du +2
This paper focuses on the continuous control of the unmanned aerial vehicle (UAV) based on a deep reinforcement learning method for a large-scale 3D complex environment. The purpos…
FEND: A Future Enhanced Distribution-Aware Contrastive Learning Framework for Long-tail Trajectory Prediction
Yuning Wang, Pu Zhang, Lei Bai +1
Predicting the future trajectories of the traffic agents is a gordian technique in autonomous driving. However, trajectory prediction suffers from data imbalance in the prevalent d…
Cognitive Accident Prediction in Driving Scenes: A Multimodality Benchmark
Jianwu Fang, Lei-Lei Li, Kuan Yang +3
Traffic accident prediction in driving videos aims to provide an early warning of the accident occurrence, and supports the decision making of safe driving systems. Previous works…
Heterogeneous Trajectory Forecasting via Risk and Scene Graph Learning
Jianwu Fang, Chen Zhu, Pu Zhang +2
Heterogeneous trajectory forecasting is critical for intelligent transportation systems, but it is challenging because of the difficulty of modeling the complex interaction relatio…
Behavioral Intention Prediction in Driving Scenes: A Survey
Jianwu Fang, Fan Wang, Jianru Xue +1
In the driving scene, the road agents usually conduct frequent interactions and intention understanding of the surroundings. Ego-agent (each road agent itself) predicts what behavi…