3 citations · 6 across the 6 of their papers we have counts for
6 papers
PRISM: PRogressive dependency maxImization for Scale-invariant image Matching
Xudong Cai, Yongcai Wang, Lun Luo +5
Image matching aims at identifying corresponding points between a pair of images. Currently, detector-free methods have shown impressive performance in challenging scenarios, thank…
ModaLink: Unifying Modalities for Efficient Image-to-PointCloud Place Recognition
Weidong Xie, Lun Luo, Nanfei Ye +7
Place recognition is an important task for robots and autonomous cars to localize themselves and close loops in pre-built maps. While single-modal sensor-based methods have shown s…
Learning A Simulation-based Visual Policy for Real-world Peg In Unseen Holes
Liang Xie, Hongxiang Yu, Kechun Xu +5
This paper proposes a learning-based visual peg-in-hole that enables training with several shapes in simulation, and adapting to arbitrary unseen shapes in real world with minimal…
Learning to Fill the Seam by Vision: Sub-millimeter Peg-in-hole on Unseen Shapes in Real World
Liang Xie, Hongxiang Yu, Yinghao Zhao +5
In the peg insertion task, human pays attention to the seam between the peg and the hole and tries to fill it continuously with visual feedback. By imitating the human behavior, we…
Robust localization for planar moving robot in changing environment: A perspective on density of correspondence and depth
Yanmei Jiao, Lilu Liu, Bo Fu +4
Visual localization for planar moving robot is important to various indoor service robotic applications. To handle the textureless areas and frequent human activities in indoor env…
Globally optimal consensus maximization for robust visual inertial localization in point and line map
Yanmei Jiao, Yue Wang, Bo Fu +4
Map based visual inertial localization is a crucial step to reduce the drift in state estimation of mobile robots. The underlying problem for localization is to estimate the pose f…