Feedbackward Decoding for Semantic Segmentation
Table 1: Cityscapes semantic segmentation results
['[BOLD] model', '[BOLD] IoU class', '[BOLD] iIoU class', '[BOLD] IoU category', '[BOLD] iIoU category', '[BOLD] params']
To be fair, we only compare our model with models that also use VGG-16 as their base network. This way we can ensure the differences in performance do not come from different choices in base models. The table shows our model significantly outperforms the other VGG-16-based models for every metric. Significantly, our model also has the smallest number of parameters.