SA-Gate is a neural network that is used for indoor segmentation. The input is a pair of an RGB image and an HHA map generated with the depth map. The output is a heat map where each pixel is predicted with a semantic category, like chair, bed, and other objects typically found indoors.
The following image shows the result of SA-Gate segmentation.
The following table lists the SA-Gate models supported by the Vitis AI Library.