32 citations · 58 across the 9 of their papers we have counts for
4 papers · 1 filter
DA-CIL: Towards Domain Adaptive Class-Incremental 3D Object Detection
Ziyuan Zhao, Mingxi Xu, Peisheng Qian +2
Deep learning has achieved notable success in 3D object detection with the advent of large-scale point cloud datasets. However, severe performance degradation in the past trained c…
Residual Skill Policies: Learning an Adaptable Skill-based Action Space for Reinforcement Learning for Robotics
Krishan Rana, Ming Xu, Brendan Tidd +2
Skill-based reinforcement learning (RL) has emerged as a promising strategy to leverage prior knowledge for accelerated robot learning. Skills are typically extracted from expert d…
Improving Worst Case Visual Localization Coverage via Place-specific Sub-selection in Multi-camera Systems
Stephen Hausler, Ming Xu, Sourav Garg +4
6-DoF visual localization systems utilize principled approaches rooted in 3D geometry to perform accurate camera pose estimation of images to a map. Current techniques use hierarch…
Improving Road Segmentation in Challenging Domains Using Similar Place Priors
Connor Malone, Sourav Garg, Ming Xu +2
Road segmentation in challenging domains, such as night, snow or rain, is a difficult task. Most current approaches boost performance using fine-tuning, domain adaptation, style tr…