  Multisensory object-centric perception, reasoning, and interaction have been
a key research topic in recent years. However, the progress in these directions
is limited by the small set of objects available -- synthetic objects are not
realistic enough and are mostly centered around geometry, while real object
datasets such as YCB are often practically challenging and unstable to acquire
due to international shipping, inventory, and financial cost. We present
ObjectFolder, a dataset of 100 virtualized objects that addresses both
challenges with two key innovations. First, ObjectFolder encodes the visual,
auditory, and tactile sensory data for all objects, enabling a number of
multisensory object recognition tasks, beyond existing datasets that focus
purely on object geometry. Second, ObjectFolder employs a uniform,
object-centric, and implicit representation for each object's visual textures,
acoustic simulations, and tactile readings, making the dataset flexible to use
and easy to share. We demonstrate the usefulness of our dataset as a testbed
for multisensory perception and control by evaluating it on a variety of
benchmark tasks, including instance recognition, cross-sensory retrieval, 3D
reconstruction, and robotic grasping.
