semantic-segmentation-pytorch - Pytorch implementation for Semantic Segmentation/Scene Parsing on MIT ADE20K dataset

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This is a PyTorch implementation of semantic segmentation models on MIT ADE20K scene parsing dataset. This module differs from the built-in PyTorch BatchNorm as the mean and standard-deviation are reduced across all devices during training. The importance of synchronized batch normalization in object detection has been recently proved with a an extensive analysis in the paper MegDet: A Large Mini-Batch Object Detector, and we empirically find that it is also important for segmentation.

http://sceneparsing.csail.mit.edu/
https://github.com/CSAILVision/semantic-segmentation-pytorch

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