2 citations · 2 across the 7 of their papers we have counts for
8 papers
SurveilNav: Collaborative Object Goal Navigation with Robot and Surveillance System
Ming-Ming Yu, Qunbo Wang, Rongtao Xu +5
With the growing deployment of surveillance systems in factories, offices, and homes, integrating them with robots offers a promising direction for collaborative and efficient task…
RailVQA: A Benchmark and Framework for Efficient Interpretable Visual Cognition in Automatic Train Operation
Sen Zhang, Runmei Li, Shizhuang Deng +7
As Automatic Train Operation (ATO) advances toward GoA4 and beyond, it increasingly depends on efficient, reliable cab-view visual perception and decision-oriented inference to ens…
UrbanNav: Learning Language-Guided Urban Navigation from Web-Scale Human Trajectories
Yanghong Mei, Yirong Yang, Longteng Guo +5
Navigating complex urban environments using natural language instructions poses significant challenges for embodied agents, including noisy language instructions, ambiguous spatial…
C-NAV: Towards Self-Evolving Continual Object Navigation in Open World
Ming-Ming Yu, Fei Zhu, Wenzhuo Liu +4
Embodied agents are expected to perform object navigation in dynamic, open-world environments. However, existing approaches typically rely on static trajectories and a fixed set of…
COSMO: Combination of Selective Memorization for Low-cost Vision-and-Language Navigation
Siqi Zhang, Yanyuan Qiao, Qunbo Wang +4
Vision-and-Language Navigation (VLN) tasks have gained prominence within artificial intelligence research due to their potential application in fields like home assistants. Many co…
FlexVLN: Flexible Adaptation for Diverse Vision-and-Language Navigation Tasks
Siqi Zhang, Yanyuan Qiao, Qunbo Wang +3
The aspiration of the Vision-and-Language Navigation (VLN) task has long been to develop an embodied agent with robust adaptability, capable of seamlessly transferring its navigati…
Self-Bootstrapped Visual-Language Model for Knowledge Selection and Question Answering
Dongze Hao, Qunbo Wang, Longteng Guo +2
While large visual-language models (LVLM) have shown promising results on traditional visual question answering benchmarks, it is still challenging for them to answer complex VQA p…
Knowledge Condensation and Reasoning for Knowledge-based VQA
Dongze Hao, Jian Jia, Longteng Guo +8
Knowledge-based visual question answering (KB-VQA) is a challenging task, which requires the model to leverage external knowledge for comprehending and answering questions grounded…