  A new event camera dataset, EVIMO2, is introduced that improves on the
popular EVIMO dataset by providing more data, from better cameras, in more
complex scenarios. As with its predecessor, EVIMO2 provides labels in the form
of per-pixel ground truth depth and segmentation as well as camera and object
poses. All sequences use data from physical cameras and many sequences feature
multiple independently moving objects. Typically, such labeled data is
unavailable in physical event camera datasets. Thus, EVIMO2 will serve as a
challenging benchmark for existing algorithms and rich training set for the
development of new algorithms. In particular, EVIMO2 is suited for supporting
research in motion and object segmentation, optical flow, structure from
motion, and visual (inertial) odometry in both monocular or stereo
configurations.
  EVIMO2 consists of 41 minutes of data from three 640$\times$480 event
cameras, one 2080$\times$1552 classical color camera, inertial measurements
from two six axis inertial measurement units, and millimeter accurate object
poses from a Vicon motion capture system. The dataset's 173 sequences are
arranged into three categories. 3.75 minutes of independently moving household
objects, 22.55 minutes of static scenes, and 14.85 minutes of basic motions in
shallow scenes. Some sequences were recorded in low-light conditions where
conventional cameras fail. Depth and segmentation are provided at 60 Hz for the
event cameras and 30 Hz for the classical camera. The masks can be regenerated
using open-source code up to rates as high as 200 Hz.
  This technical report briefly describes EVIMO2. The full documentation is
available online. Videos of individual sequences can be sampled on the download
page.
