Severity-Aware Semantic Segmentation With Reinforced Wasserstein Training

Semantic segmentation is a class of methods to classify each pixel in an image into semantic classes, which is critical for autonomous vehicles and surgery systems. Cross-entropy (CE) loss-based deep neural networks (DNN) achieved great success w.r.t... (read more)

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Methods used in the Paper


METHOD TYPE
CARLA
Video Game Models
Dense Connections
Feedforward Networks
Feedforward Network
Feedforward Networks
Dilated Convolution
Convolutions
CRF
Structured Prediction
DeepLab
Semantic Segmentation Models