On the Importance of Stereo for Accurate Depth Estimation: An Efficient Semi-Supervised Deep Neural Network Approach

Understand

We revisit the problem of visual depth estimation in the context of autonomous vehicles.

• Despite the progress on monocular depth estimation in recent years, we show that the gap between monocular and stereo depth accuracy remains large$-$a particularly relevant result due to the prevalent reliance upon monocular cameras by vehicles that are expected to be self-driving.
• We argue that the challenges of removing this gap are significant, owing to fundamental limitations of monocular vision.
• As a result, we focus our efforts on depth estimation by stereo.