A point cloud is a set of points defined in a 3D metric space. Point clouds have become one
of the most significant data formats for 3D representation and are gaining increased …

Building home assistant robots has long been a goal for vision and robotics researchers. To
achieve this task, a simulated environment with physically realistic simulation, sufficient …

For years, researchers have been devoted to generalizable object perception and
manipulation, where cross-category generalizability is highly desired yet underexplored. In …

Articulated object manipulation is a fundamental yet challenging task in robotics. Due to
significant geometric and semantic variations across object categories, previous …

One of the fundamental goals of visual perception is to allow agents to meaningfully interact
with their environment. In this paper, we take a step towards that long-term goal--we extract …

Perceiving and manipulating 3D articulated objects in diverse environments is essential for
home-assistant robots. Recent studies have shown that point-level affordance provides …

Existing 3D scene understanding methods are heavily focused on 3D semantic and instance
segmentation. However identifying objects and their parts only constitutes an intermediate …

We present iGibson 1.0, a novel simulation environment to develop robotic solutions for
interactive tasks in large-scale realistic scenes. Our environment contains 15 fully interactive …

Digitizing physical objects into the virtual world has the potential to unlock new research and
applications in embodied AI and mixed reality. This work focuses on recreating interactive …

This paper addresses the task of category-level pose estimation for articulated objects from
a single depth image. We present a novel category-level approach that correctly …