Method Details

Details for method 'Spatial Sampling Net'

name	Spatial Sampling Net
challenge	pixel-level semantic labeling
details	We propose a network architecture to perform efficient scene understanding. This work presents three main novelties: the first is an Improved Guided Upsampling Module that can replace in toto the decoder part in common semantic segmentation networks. Our second contribution is the introduction of a new module based on spatial sampling to perform Instance Segmentation. It provides a very fast instance segmentation, needing only thresholding as post-processing step at inference time. Finally, we propose a novel efficient network design that includes the new modules and we test it against different datasets for outdoor scene understanding.
publication	Spatial Sampling Network for Fast Scene Understanding Davide Mazzini, Raimondo Schettini CVPR 2019 Workshop on Autonomous Driving http://openaccess.thecvf.com/content_CVPRW_2019/html/WAD/Mazzini_Spatial_Sampling_Network_for_Fast_Scene_Understanding_CVPRW_2019_paper.html
project page / code
used Cityscapes data	fine annotations
used external data	ImageNet
runtime	0.00884 s Titan Xp GPU
subsampling	2
submission date	November, 2018
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