6 citations · 15 across the 12 of their papers we have counts for
13 papers
Human Behavior-Informed Crash Scenario Generation with Real-World Crash Priors for Autonomous Vehicle Safety Evaluation
Mingxing Peng, Xusen Guo, Long Chen +3
Reliable safety evaluation of autonomous vehicles (AVs) is essential to improving road safety, yet it depends critically on realistic simulation of rare crashes. Existing crash sce…
SpikeVLA: Vision-Language-Action Models with Spiking Neural Networks
Ruiqi Song, Dujun Nie, Siyu Teng +7
Vision-Language-Action (VLA) models have become a dominant paradigm for embodied intelligence. However, most existing approaches are built on large-scale transformers, resulting in…
StereoCarla: A High-Fidelity Driving Dataset for Generalizable Stereo
Xianda Guo, Chenming Zhang, Ruilin Wang +6
Stereo matching plays a crucial role in enabling depth perception for autonomous driving and robotics. While recent years have witnessed remarkable progress in stereo matching algo…
InsightDrive: Insight Scene Representation for End-to-End Autonomous Driving
Ruiqi Song, Xianda Guo, Yanlun Peng +3
Conventional end-to-end autonomous driving methods often rely on explicit global scene representations, which typically consist of 3D object detection, online mapping, and motion p…
WMNav: Integrating Vision-Language Models into World Models for Object Goal Navigation
Dujun Nie, Xianda Guo, Yiqun Duan +2
Object Goal Navigation-requiring an agent to locate a specific object in an unseen environment-remains a core challenge in embodied AI. Although recent progress in Vision-Language…
Stereo Anything: Unifying Zero-shot Stereo Matching with Large-Scale Mixed Data
Xianda Guo, Chenming Zhang, Youmin Zhang +8
Stereo matching serves as a cornerstone in 3D vision, aiming to establish pixel-wise correspondences between stereo image pairs for depth recovery. Despite remarkable progress driv…
SURDS: Benchmarking Spatial Understanding and Reasoning in Driving Scenarios with Vision Language Models
Xianda Guo, Ruijun Zhang, Yiqun Duan +7
Accurate spatial reasoning in outdoor environments - covering geometry, object pose, and inter-object relationships - is fundamental to downstream tasks such as mapping, motion for…
AdvDiffuser: Generating Adversarial Safety-Critical Driving Scenarios via Guided Diffusion
Yuting Xie, Xianda Guo, Cong Wang +2
Safety-critical scenarios are infrequent in natural driving environments but hold significant importance for the training and testing of autonomous driving systems. The prevailing…
Instruct Large Language Models to Drive like Humans
Ruijun Zhang, Xianda Guo, Wenzhao Zheng +3
Motion planning in complex scenarios is the core challenge in autonomous driving. Conventional methods apply predefined rules or learn from driving data to plan the future trajecto…
LightStereo: Channel Boost Is All You Need for Efficient 2D Cost Aggregation
Xianda Guo, Chenming Zhang, Youmin Zhang +4
We present LightStereo, a cutting-edge stereo-matching network crafted to accelerate the matching process. Departing from conventional methodologies that rely on aggregating comput…
GenAD: Generative End-to-End Autonomous Driving
Wenzhao Zheng, Ruiqi Song, Xianda Guo +2
Directly producing planning results from raw sensors has been a long-desired solution for autonomous driving and has attracted increasing attention recently. Most existing end-to-e…
OpenStereo: A Comprehensive Benchmark for Stereo Matching and Strong Baseline
Xianda Guo, Chenming Zhang, Juntao Lu +5
Stereo matching aims to estimate the disparity between matching pixels in a stereo image pair, which is important to robotics, autonomous driving, and other computer vision tasks.…
Adjacent-view Transformers for Supervised Surround-view Depth Estimation
Xianda Guo, Wenjie Yuan, Yunpeng Zhang +5
Depth estimation has been widely studied and serves as the fundamental step of 3D perception for robotics and autonomous driving. Though significant progress has been made in monoc…