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Found 4 papers, 1 papers with code
APE: An Open and Shared Annotated Dataset for Learning Urban Pedestrian Path Networks
The process features the use of a multi-input segmentation network trained on our dataset to predict important classes in the pedestrian environment and then generate a connected pedestrian path network.
OASIS: Automated Assessment of Urban Pedestrian Paths at Scale
The inspection of the Public Right of Way (PROW) for accessibility barriers is necessary for monitoring and maintaining the built environment for communities' walkability, rollability, safety, active transportation, and sustainability.
Rethinking Semantic Segmentation Evaluation for Explainability and Model Selection
Semantic segmentation is a prerequisite for this task since it maps contiguous regions of the same class as single entities.
ESPNet: Efficient Spatial Pyramid of Dilated Convolutions for Semantic Segmentation
We introduce a fast and efficient convolutional neural network, ESPNet, for semantic segmentation of high resolution images under resource constraints.
Ranked #48 on
Semantic Segmentation
on PASCAL VOC 2012 test
