An Unsupervised Temporal Consistency (TC) Loss to Improve the Performance of Semantic Segmentation Networks

Deep neural networks (DNNs) for highly automated driving are often trained on a large and diverse dataset, and evaluation metrics are reported usually on a per-frame basis. However, when evaluated on video sequences, the predictions are often unstable between consecutive frames. As such unstable predictions over time can lead to severe safety consequences, there is a growing need to understand, ev...