collaborators

6 papers

cs.RO2026

Persistent Autoregressive Mapping with Traffic Rules for Autonomous Driving

Shiyi Liang, Xinyuan Chang, Changjie Wu +8

Safe autonomous driving requires both accurate HD map construction and persistent awareness of traffic rules, even when their associated signs are no longer visible. However, exist…

cs.CV2026

Seeing Space and Motion: Enhancing Latent Actions with Geometric and Dynamic Awareness for Vision-Language-Action Models

Zhejia Cai, Yandan Yang, Xinyuan Chang +5

Latent Action Models (LAMs) enable Vision- Language-Action (VLA) systems to learn semantic action representations from large-scale unannotated data. Yet, we identify two bottleneck…

cs.CV2026

FARTrack: Fast Autoregressive Visual Tracking with High Performance

Guijie Wang, Tong Lin, Yifan Bai +4

Inference speed and tracking performance are two critical evaluation metrics in the field of visual tracking. However, high-performance trackers often suffer from slow processing s…

cs.CV2026

JanusVLN: Decoupling Semantics and Spatiality with Dual Implicit Memory for Vision-Language Navigation

Shuang Zeng, Dekang Qi, Xinyuan Chang +7

Vision-and-Language Navigation requires an embodied agent to navigate through unseen environments, guided by natural language instructions and a continuous video stream. Recent adv…

cs.CV2025

PriorDrive: Enhancing Online HD Mapping with Unified Vector Priors

Shuang Zeng, Xinyuan Chang, Xinran Liu +5

High-Definition Maps (HD maps) are essential for the precise navigation and decision-making of autonomous vehicles, yet their creation and upkeep present significant cost and timel…

cs.CV2025

UniMapGen: A Generative Framework for Large-Scale Map Construction from Multi-modal Data

Yujian Yuan, Changjie Wu, Xinyuan Chang +6

Large-scale map construction plays a vital role in applications like autonomous driving and navigation systems. Traditional large-scale map construction approaches mainly rely on c…