15 papers
UECP: Uncertainty-Enhanced Collaborative Perception
Kang Yang, Tianci Bu, Peng Wang +3
Collaborative perception serves as a pivotal solution to enhance the perception capability of individual agents in autonomous driving, where a core challenge lies in seeking reliab…
MapDream: Task-Driven Map Learning for Vision-Language Navigation
Guoxin Lian, Shuo Wang, Yucheng Wang +7
Vision-Language Navigation (VLN) requires agents to follow natural language instructions in partially observed 3D environments, motivating map representations that aggregate spatia…
BOLT: Online Lightweight Adaptation for Preparation-Free Heterogeneous Cooperative Perception
Kang Yang, Tianci Bu, Peng Wang +2
Most existing heterogeneous cooperative perception methods depend on prior preparation like offline joint training or tailored collaborator-model adaptation. Such preprocessing is,…
Progress-Think: Semantic Progress Reasoning for Vision-Language Navigation
Shuo Wang, Yucheng Wang, Guoxin Lian +9
Vision-Language Navigation requires agents to act coherently over long horizons by understanding not only local visual context but also how far they have advanced within a multi-st…
EIMC: Efficient Instance-aware Multi-modal Collaborative Perception
Kang Yang, Peng Wang, Lantao Li +4
Multi-modal collaborative perception calls for great attention to enhancing the safety of autonomous driving. However, current multi-modal approaches remain a ``local fusion to com…
MonoDream: Monocular Vision-Language Navigation with Panoramic Dreaming
Shuo Wang, Yongcai Wang, Zhaoxin Fan +8
Vision-Language Navigation (VLN) tasks often leverage panoramic RGB and depth inputs to provide rich spatial cues for action planning, but these sensors can be costly or less acces…