>For instance, convolutional neural networks trained on millions of images can fail when they see objects under new lighting conditions or from slightly different angles or against new backgrounds.

The big picture is humans use a multi-task network for depth, segmentation (and background removal), lighting source estimation (and shadow removal), material extraction, SLAM (and geometry reconstruction), optical flow, etc. Papers and their networks only look at a small part of what humans do; we are not just using a single "neural network."