  Gated cameras flood-illuminate a scene and capture the time-gated impulse
response of a scene. By employing nanosecond-scale gates, existing sensors are
capable of capturing mega-pixel gated images, delivering dense depth improving
on today's LiDAR sensors in spatial resolution and depth precision. Although
gated depth estimation methods deliver a million of depth estimates per frame,
their resolution is still an order below existing RGB imaging methods. In this
work, we combine high-resolution stereo HDR RCCB cameras with gated imaging,
allowing us to exploit depth cues from active gating, multi-view RGB and
multi-view NIR sensing -- multi-view and gated cues across the entire spectrum.
The resulting capture system consists only of low-cost CMOS sensors and
flood-illumination. We propose a novel stereo-depth estimation method that is
capable of exploiting these multi-modal multi-view depth cues, including the
active illumination that is measured by the RCCB camera when removing the
IR-cut filter. The proposed method achieves accurate depth at long ranges,
outperforming the next best existing method by 39% for ranges of 100 to 220m in
MAE on accumulated LiDAR ground-truth. Our code, models and datasets are
available at https://light.princeton.edu/gatedrccbstereo/ .
