Application of Vision-Language Model to Pedestrians Behavior and Scene Understanding in Autonomous Driving
Fuente:
arXiv
Saved in:
| Main Authors: | Gao, Haoxiang, Zhang, Li, Zhao, Yu, Yang, Zhou, Cao, Jinghan |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
An Expert Ensemble for Detecting Anomalous Scenes, Interactions, and Behaviors in Autonomous Driving
by: Ji, Tianchen, et al.
Published: (2025)
by: Ji, Tianchen, et al.
Published: (2025)
VECTOR-Drive: Tightly Coupled Vision-Language and Trajectory Expert Routing for End-to-End Autonomous Driving
by: Zhao, Rui, et al.
Published: (2026)
by: Zhao, Rui, et al.
Published: (2026)
Natural Language Instructions for Scene-Responsive Human-in-the-Loop Motion Planning in Autonomous Driving using Vision-Language-Action Models
by: Martinez-Sanchez, Angel, et al.
Published: (2026)
by: Martinez-Sanchez, Angel, et al.
Published: (2026)
Vision and Language: Novel Representations and Artificial intelligence for Driving Scene Safety Assessment and Autonomous Vehicle Planning
by: Greer, Ross, et al.
Published: (2026)
by: Greer, Ross, et al.
Published: (2026)
DiffVLA: Vision-Language Guided Diffusion Planning for Autonomous Driving
by: Jiang, Anqing, et al.
Published: (2025)
by: Jiang, Anqing, et al.
Published: (2025)
A Survey on Vision-Language-Action Models for Autonomous Driving
by: Jiang, Sicong, et al.
Published: (2025)
by: Jiang, Sicong, et al.
Published: (2025)
Perception Without Vision for Trajectory Prediction: Ego Vehicle Dynamics as Scene Representation for Efficient Active Learning in Autonomous Driving
by: Greer, Ross, et al.
Published: (2024)
by: Greer, Ross, et al.
Published: (2024)
Less is More: Lean yet Powerful Vision-Language Model for Autonomous Driving
by: Yang, Sheng, et al.
Published: (2025)
by: Yang, Sheng, et al.
Published: (2025)
DriveMoE: Mixture-of-Experts for Vision-Language-Action Model in End-to-End Autonomous Driving
by: Yang, Zhenjie, et al.
Published: (2025)
by: Yang, Zhenjie, et al.
Published: (2025)
DeeAD: Dynamic Early Exit of Vision-Language Action for Efficient Autonomous Driving
by: HU, Haibo, et al.
Published: (2025)
by: HU, Haibo, et al.
Published: (2025)
A Low-Rank Method for Vision Language Model Hallucination Mitigation in Autonomous Driving
by: Long, Keke, et al.
Published: (2025)
by: Long, Keke, et al.
Published: (2025)
SceneVerse: Scaling 3D Vision-Language Learning for Grounded Scene Understanding
by: Jia, Baoxiong, et al.
Published: (2024)
by: Jia, Baoxiong, et al.
Published: (2024)
DriveGPT: Scaling Autoregressive Behavior Models for Driving
by: Huang, Xin, et al.
Published: (2024)
by: Huang, Xin, et al.
Published: (2024)
Pedestrian Intention Prediction via Vision-Language Foundation Models
by: Azarmi, Mohsen, et al.
Published: (2025)
by: Azarmi, Mohsen, et al.
Published: (2025)
Enhancing Vision-Language Models with Scene Graphs for Traffic Accident Understanding
by: Lohner, Aaron, et al.
Published: (2024)
by: Lohner, Aaron, et al.
Published: (2024)
HiST-VLA: A Hierarchical Spatio-Temporal Vision-Language-Action Model for End-to-End Autonomous Driving
by: Wang, Yiru, et al.
Published: (2026)
by: Wang, Yiru, et al.
Published: (2026)
STT: Stateful Tracking with Transformers for Autonomous Driving
by: Jing, Longlong, et al.
Published: (2024)
by: Jing, Longlong, et al.
Published: (2024)
DriveCritic: Towards Context-Aware, Human-Aligned Evaluation for Autonomous Driving with Vision-Language Models
by: Song, Jingyu, et al.
Published: (2025)
by: Song, Jingyu, et al.
Published: (2025)
Behavioral Cloning Models Reality Check for Autonomous Driving
by: Yildirim, Mustafa, et al.
Published: (2024)
by: Yildirim, Mustafa, et al.
Published: (2024)
What Matters to Enhance Traffic Rule Compliance of Imitation Learning for End-to-End Autonomous Driving
by: Zhou, Hongkuan, et al.
Published: (2023)
by: Zhou, Hongkuan, et al.
Published: (2023)
Pseudo-Simulation for Autonomous Driving
by: Cao, Wei, et al.
Published: (2025)
by: Cao, Wei, et al.
Published: (2025)
GarchingSim: An Autonomous Driving Simulator with Photorealistic Scenes and Minimalist Workflow
by: Zhou, Liguo, et al.
Published: (2024)
by: Zhou, Liguo, et al.
Published: (2024)
DriveVLM-RL: Neuroscience-Inspired Reinforcement Learning with Vision-Language Models for Safe and Deployable Autonomous Driving
by: Huang, Zilin, et al.
Published: (2026)
by: Huang, Zilin, et al.
Published: (2026)
DVGT-2: Vision-Geometry-Action Model for Autonomous Driving at Scale
by: Zuo, Sicheng, et al.
Published: (2026)
by: Zuo, Sicheng, et al.
Published: (2026)
DepthVision: Enabling Robust Vision-Language Models with GAN-Based LiDAR-to-RGB Synthesis for Autonomous Driving
by: Kirchner, Sven, et al.
Published: (2025)
by: Kirchner, Sven, et al.
Published: (2025)
STELLAR: Scaling 3D Perception Large Models for Autonomous Driving
by: Li, Yingwei, et al.
Published: (2026)
by: Li, Yingwei, et al.
Published: (2026)
Continuous Vision-Language-Action Co-Learning with Semantic-Physical Alignment for Behavioral Cloning
by: Qi, Xiuxiu, et al.
Published: (2025)
by: Qi, Xiuxiu, et al.
Published: (2025)
Exploring the Interplay Between Video Generation and World Models in Autonomous Driving: A Survey
by: Fu, Ao, et al.
Published: (2024)
by: Fu, Ao, et al.
Published: (2024)
Text-Scene: A Scene-to-Language Parsing Framework for 3D Scene Understanding
by: Li, Haoyuan, et al.
Published: (2025)
by: Li, Haoyuan, et al.
Published: (2025)
RAD-LAD: Rule and Language Grounded Autonomous Driving in Real-Time
by: Ghosh, Anurag, et al.
Published: (2026)
by: Ghosh, Anurag, et al.
Published: (2026)
VLM-RL: A Unified Vision Language Models and Reinforcement Learning Framework for Safe Autonomous Driving
by: Huang, Zilin, et al.
Published: (2024)
by: Huang, Zilin, et al.
Published: (2024)
A Survey for Foundation Models in Autonomous Driving
by: Gao, Haoxiang, et al.
Published: (2024)
by: Gao, Haoxiang, et al.
Published: (2024)
ReconDreamer: Crafting World Models for Driving Scene Reconstruction via Online Restoration
by: Ni, Chaojun, et al.
Published: (2024)
by: Ni, Chaojun, et al.
Published: (2024)
DrivingGen: A Comprehensive Benchmark for Generative Video World Models in Autonomous Driving
by: Zhou, Yang, et al.
Published: (2026)
by: Zhou, Yang, et al.
Published: (2026)
SEAL: Vision-Language Model-Based Safe End-to-End Cooperative Autonomous Driving with Adaptive Long-Tail Modeling
by: You, Junwei, et al.
Published: (2025)
by: You, Junwei, et al.
Published: (2025)
LanguageMPC: Large Language Models as Decision Makers for Autonomous Driving
by: Sha, Hao, et al.
Published: (2023)
by: Sha, Hao, et al.
Published: (2023)
Copilot4D: Learning Unsupervised World Models for Autonomous Driving via Discrete Diffusion
by: Zhang, Lunjun, et al.
Published: (2023)
by: Zhang, Lunjun, et al.
Published: (2023)
Controllable Pedestrian Video Editing for Multi-View Driving Scenarios via Motion Sequence
by: Fu, Danzhen, et al.
Published: (2025)
by: Fu, Danzhen, et al.
Published: (2025)
CurricuVLM: Towards Safe Autonomous Driving via Personalized Safety-Critical Curriculum Learning with Vision-Language Models
by: Sheng, Zihao, et al.
Published: (2025)
by: Sheng, Zihao, et al.
Published: (2025)
DarkQA: Benchmarking Vision-Language Models on Visual-Primitive Question Answering in Low-Light Indoor Scenes
by: Park, Yohan, et al.
Published: (2025)
by: Park, Yohan, et al.
Published: (2025)
Similar Items
-
An Expert Ensemble for Detecting Anomalous Scenes, Interactions, and Behaviors in Autonomous Driving
by: Ji, Tianchen, et al.
Published: (2025) -
VECTOR-Drive: Tightly Coupled Vision-Language and Trajectory Expert Routing for End-to-End Autonomous Driving
by: Zhao, Rui, et al.
Published: (2026) -
Natural Language Instructions for Scene-Responsive Human-in-the-Loop Motion Planning in Autonomous Driving using Vision-Language-Action Models
by: Martinez-Sanchez, Angel, et al.
Published: (2026) -
Vision and Language: Novel Representations and Artificial intelligence for Driving Scene Safety Assessment and Autonomous Vehicle Planning
by: Greer, Ross, et al.
Published: (2026) -
DiffVLA: Vision-Language Guided Diffusion Planning for Autonomous Driving
by: Jiang, Anqing, et al.
Published: (2025)