1 citations · 1 across the 5 of their papers we have counts for
5 papers
RoSHI: A Versatile Robot-oriented Suit for Human Data In-the-Wild
Wenjing Margaret Mao, Jefferson Ng, Luyang Hu +2
Scaling up robot learning will likely require human data containing rich and long-horizon interactions in the wild. Existing approaches for collecting such data trade off portabili…
A Linear N-Point Solver for Structure and Motion from Asynchronous Tracks
Hang Su, Yunlong Feng, Daniel Gehrig +4
Structure and continuous motion estimation from point correspondences is a fundamental problem in computer vision that has been powered by well-known algorithms such as the familia…
Neural Inertial Odometry from Lie Events
Royina Karegoudra Jayanth, Yinshuang Xu, Evangelos Chatzipantazis +2
Neural displacement priors (NDP) can reduce the drift in inertial odometry and provide uncertainty estimates that can be readily fused with off-the-shelf filters. However, they fai…
ETAP: Event-based Tracking of Any Point
Friedhelm Hamann, Daniel Gehrig, Filbert Febryanto +2
Tracking any point (TAP) recently shifted the motion estimation paradigm from focusing on individual salient points with local templates to tracking arbitrary points with global im…
EqNIO: Subequivariant Neural Inertial Odometry
Royina Karegoudra Jayanth, Yinshuang Xu, Ziyun Wang +3
Neural networks are seeing rapid adoption in purely inertial odometry, where accelerometer and gyroscope measurements from commodity inertial measurement units (IMU) are used to re…