While neural rendering has demonstrated impressive capabilities in 3D scene
reconstruction and novel view synthesis, it heavily relies on high-quality sharp images and …

An open research question in robotics is how to combine the benefits of model-free
reinforcement learning (RL)—known for its strong task performance and flexibility in …

Over the last decade, the use of autonomous drone systems for surveying, search and
rescue, or last-mile delivery has increased exponentially. With the rise of these applications …

We present EgoHDM, an online egocentric-inertial human motion capture (mocap),
localization, and dense map** system. Our system uses 6 inertial measurement units …

Deep Equilibrium (DEQ) Models, an emerging class of implicit models that maps inputs to
fixed points of neural networks, are of growing interest in the deep learning community …

This paper introduces a robust unsupervised SE (3) point cloud registration method that
operates without requiring point correspondences. The method frames point clouds as …

This paper explores the problem of collision-free motion generation for manipulators by
formulating it as a global motion optimization problem. We develop a parallel optimization …