1 citations · 2 across the 6 of their papers we have counts for
6 papers
DriveCombo: Benchmarking Compositional Traffic Rule Reasoning in Autonomous Driving
Enhui Ma, Jiahuan Zhang, Guantian Zheng +10
Multimodal Large Language Models (MLLMs) are rapidly becoming the intelligence brain of end-to-end autonomous driving systems. A key challenge is to assess whether MLLMs can truly…
OmniScene: Attention-Augmented Multimodal 4D Scene Understanding for Autonomous Driving
Pei Liu, Hongliang Lu, Haichao Liu +5
Human vision is capable of transforming two-dimensional observations into an egocentric three-dimensional scene understanding, which underpins the ability to translate complex scen…
Beyond conventional vision: RGB-event fusion for robust object detection in dynamic traffic scenarios
Zhanwen Liu, Yujing Sun, Yang Wang +3
The dynamic range limitation of conventional RGB cameras reduces global contrast and causes loss of high-frequency details such as textures and edges in complex traffic environment…
Hierarchical End-to-End Autonomous Driving: Integrating BEV Perception with Deep Reinforcement Learning
Siyi Lu, Lei He, Shengbo Eben Li +3
End-to-end autonomous driving offers a streamlined alternative to the traditional modular pipeline, integrating perception, prediction, and planning within a single framework. Whil…
Vision-Driven 2D Supervised Fine-Tuning Framework for Bird's Eye View Perception
Lei He, Qiaoyi Wang, Honglin Sun +5
Visual bird's eye view (BEV) perception, due to its excellent perceptual capabilities, is progressively replacing costly LiDAR-based perception systems, especially in the realm of…
Quantitative Representation of Scenario Difficulty for Autonomous Driving Based on Adversarial Policy Search
Shuo Yang, Caojun Wang, Yuanjian Zhang +4
Adversarial scenario generation is crucial for autonomous driving testing because it can efficiently simulate various challenge and complex traffic conditions. However, it is diffi…