We present a near real-time (10Hz) method for 6-DoF tracking of an unknown object from a
monocular RGBD video sequence, while simultaneously performing neural 3D …

Object pose estimation is a core perception task that enables, for example, object
manipulation and scene understanding. The widely available, inexpensive, and high …

Recently, 6DoF object pose estimation has become increasingly important for a broad range
of applications in the fields of virtual reality, augmented reality, autonomous driving, and …

We propose a new method for object pose estimation without CAD models. The previous
feature-matching-based method OnePose has shown promising results under a one-shot …

We introduce MegaPose, a method to estimate the 6D pose of novel objects, that is, objects
unseen during training. At inference time, the method only assumes knowledge of (i) a …

We propose FoundPose, a model-based method for 6D pose estimation of unseen objects
from a single RGB image. The method can quickly onboard new objects using their 3D …

Capturing the interactions between humans and their environment in 3D is important for
many applications in robotics, graphics, and vision. Recent works to reconstruct the 3D …

Zero-shot 6D object pose estimation involves the detection of novel objects with their 6D
poses in cluttered scenes presenting significant challenges for model generalizability …

We present a parallelized optimization method based on fast Neural Radiance Fields
(NeRF) for estimating 6-DoF pose of a camera with respect to an object or scene. Given a …

Imitation learning from a large set of human demonstrations has proved to be an effective
paradigm for building capable robot agents. However, the demonstrations can be extremely …