3 papers
cs.CV2026
VIMD: Monocular Visual-Inertial Motion and Depth Estimation
Saimouli Katragadda, Guoquan Huang
Accurate and efficient dense metric depth estimation is crucial for 3D visual perception in robotics and XR. In this paper, we develop a monocular visual-inertial motion and depth…
cs.AI2025
Online Language Splatting
Saimouli Katragadda, Cho-Ying Wu, Yuliang Guo +3
To enable AI agents to interact seamlessly with both humans and 3D environments, they must not only perceive the 3D world accurately but also align human language with 3D spatial r…
cs.RO2025
Learning IMU Bias with Diffusion Model
Shenghao Zhou, Saimouli Katragadda, Guoquan Huang
Motion sensing and tracking with IMU data is essential for spatial intelligence, which however is challenging due to the presence of time-varying stochastic bias. IMU bias is affec…