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cs.CV2026
SpaAct: Spatially-Activated Transition Learning with Curriculum Adaptation for Vision-Language Navigation
Pengna Li, Kangyi Wu, Shaoqing Xu +7
Vision-and-Language Navigation (VLN) aims to enable an embodied agent to follow natural-language instructions and navigate to a target location in unseen 3D environments. We argue…
cs.CV2026
VILTA: A VLM-in-the-Loop Adversary for Enhancing Driving Policy Robustness
Qimao Chen, Fang Li, Shaoqing Xu +9
The safe deployment of autonomous driving (AD) systems is fundamentally hindered by the long-tail problem, where rare yet critical driving scenarios are severely underrepresented i…
cs.CV2025
DVGT: Driving Visual Geometry Transformer
Sicheng Zuo, Zixun Xie, Wenzhao Zheng +6
Perceiving and reconstructing 3D scene geometry from visual inputs is crucial for autonomous driving. However, there still lacks a driving-targeted dense geometry perception model…