2 citations · 2 across the 6 of their papers we have counts for
7 papers
ImagineNav++: Prompting Vision-Language Models as Embodied Navigator through Scene Imagination
Teng Wang, Xinxin Zhao, Wenzhe Cai +1
Visual navigation is a fundamental capability for autonomous home-assistance robots, enabling long-horizon tasks such as object search. While recent methods have leveraged Large La…
A Modern Look at Simplicity Bias in Image Classification Tasks
Xiaoguang Chang, Teng Wang, Changyin Sun
The simplicity Bias (SB) of neural networks, i.e.\ their tendency to represent simple functions, is a key factor in their generalization capabilities. Recent studies show that an e…
EDCFlow: Exploring Temporally Dense Difference Maps for Event-based Optical Flow Estimation
Daikun Liu, Lei Cheng, Teng Wang +1
Recent learning-based methods for event-based optical flow estimation utilize cost volumes for pixel matching but suffer from redundant computations and limited scalability to high…
ImagineNav: Prompting Vision-Language Models as Embodied Navigator through Scene Imagination
Xinxin Zhao, Wenzhe Cai, Likun Tang +1
Visual navigation is an essential skill for home-assistance robots, providing the object-searching ability to accomplish long-horizon daily tasks. Many recent approaches use Large…
Window-to-Window BEV Representation Learning for Limited FoV Cross-View Geo-localization
Lei Cheng, Teng Wang, Lingquan Meng +1
Cross-view geo-localization confronts significant challenges due to large perspective changes, especially when the ground-view query image has a limited field of view with unknown…
LVLM-empowered Multi-modal Representation Learning for Visual Place Recognition
Teng Wang, Lingquan Meng, Lei Cheng +1
Visual place recognition (VPR) remains challenging due to significant viewpoint changes and appearance variations. Mainstream works tackle these challenges by developing various fe…
DGMem: Learning Visual Navigation Policy without Any Labels by Dynamic Graph Memory
Wenzhe Cai, Teng Wang, Guangran Cheng +2
In recent years, learning-based approaches have demonstrated significant promise in addressing intricate navigation tasks. Traditional methods for training deep neural network navi…