1 citations · 2 across the 11 of their papers we have counts for
12 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…
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…
2COOOL: 2nd Workshop on the Challenge Of Out-Of-Label Hazards in Autonomous Driving
Ali K. AlShami, Ryan Rabinowitz, Maged Shoman +9
As the computer vision community advances autonomous driving algorithms, integrating vision-based insights with sensor data remains essential for improving perception, decision mak…
Causal-Entity Reflected Egocentric Traffic Accident Video Synthesis
Lei-lei Li, Jianwu Fang, Junbin Xiao +5
Egocentricly comprehending the causes and effects of car accidents is crucial for the safety of self-driving cars, and synthesizing causal-entity reflected accident videos can faci…
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…
Accelerate 3D Object Detection Models via Zero-Shot Attention Key Pruning
Lizhen Xu, Xiuxiu Bai, Xiaojun Jia +2
Query-based methods with dense features have demonstrated remarkable success in 3D object detection tasks. However, the computational demands of these models, particularly with lar…
Monocular Lane Detection Based on Deep Learning: A Survey
Xin He, Haiyun Guo, Kuan Zhu +4
Lane detection plays an important role in autonomous driving perception systems. As deep learning algorithms gain popularity, monocular lane detection methods based on them have de…
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…
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…