2 citations · 3 across the 8 of their papers we have counts for
4 papers · 1 filter
SUMO: Segment and Track Any Motion with Nonlinear State Space Models
Kexin Tian, Sixu Li, Keshu Wu +2
Visual Object Tracking (VOT) and Moving Object Segmentation (MOS) are two fundamental tasks in computer vision that involve both spatial and temporal object dynamics. Existing meth…
NuScenes-SpatialQA: A Spatial Understanding and Reasoning Benchmark for Vision-Language Models in Autonomous Driving
Kexin Tian, Jingrui Mao, Yunlong Zhang +3
Recent advancements in Vision-Language Models (VLMs) have demonstrated strong potential for autonomous driving tasks. However, their spatial understanding and reasoning-key capabil…
OpenEMMA: Open-Source Multimodal Model for End-to-End Autonomous Driving
Shuo Xing, Chengyuan Qian, Yuping Wang +4
Since the advent of Multimodal Large Language Models (MLLMs), they have made a significant impact across a wide range of real-world applications, particularly in Autonomous Driving…
AutoTrust: Benchmarking Trustworthiness in Large Vision Language Models for Autonomous Driving
Shuo Xing, Hongyuan Hua, Xiangbo Gao +10
Recent advancements in large vision language models (VLMs) tailored for autonomous driving (AD) have shown strong scene understanding and reasoning capabilities, making them undeni…