Release of DenseTorch

I have just released a PyTorch wrapper that aims to facilitate a typical training workflow of dense per-pixel tasks. The project code is available here. Currently, two training examples are provided: one for single-task training of semantic segmentation using DeepLab-v3+ with the Xception65 backbone, and one for multi-task training of joint semantic segmentation and depth estimation using Multi-Task RefineNet with the MobileNet-v2 backbone.

More examples and features will be gradually added!

Written on May 4, 2019