7 citations · 7 across the 14 of their papers we have counts for
6 papers · 1 filter
HexVIO: Towards All-Day Stereo-Inertial Tracking Through Commodity DSPs
Patrick Wolf, Mateo de Mayo, Daniel Cremers
The ability of a device to localize itself within its surroundings is a fundamental prerequisite for spatial computing. Visual-inertial odometry (VIO) has proven to be a cost-effec…
VkVIO: Cross-platform GPU Acceleration for Visual-Inertial Odometry with Vulkan
Ole Hoffmann, Mateo de Mayo, Daniel Cremers
Perception in robotics and XR fundamentally relies on good state estimation. Visual-inertial odometry (VIO) and Simultaneous Localization and Mapping (VI-SLAM) are proven ways of a…
Stipple: Real-Time Incremental Gaussian Splatting with Visual-Inertial Tracking
Kilian Northoff, Mateo de Mayo, Daniel Cremers
3D Gaussian Splatting (3DGS) provides efficient rendering of photo-realistic scenes, but its heavy preprocessing and training steps make it a poor fit for applications that require…
Robot Self-Improvement via Human-Video Dynamics Models
Hanzhi Chen, Anran Zhang, Simon Schaefer +5
A central question in robot learning is how to acquire skills from the kinds of data that humans learn from: passive observation, embodied practice, and the experience of failure.…
PG-SLAM: Photo-realistic and Geometry-aware RGB-D SLAM in Dynamic Environments
Haoang Li, Xiangqi Meng, Xingxing Zuo +3
Simultaneous localization and mapping (SLAM) has achieved impressive performance in static environments. However, SLAM in dynamic environments remains an open question. Many method…
HI-SLAM2: Geometry-Aware Gaussian SLAM for Fast Monocular Scene Reconstruction
Wei Zhang, Qing Cheng, David Skuddis +3
We present HI-SLAM2, a geometry-aware Gaussian SLAM system that achieves fast and accurate monocular scene reconstruction using only RGB input. Existing Neural SLAM or 3DGS-based S…