Bilateral Grid Learning for Stereo Matching Networks

1 Jan 2021 Bin Xu Yuhua Xu Xiaoli Yang Wei Jia Yulan Guo

Real-time performance of stereo matching networks is important for many applications, such as automatic driving, robot navigation and augmented reality (AR). Although significant progress has been made in stereo matching networks in recent years, it is still challenging to balance real-time performance and accuracy... (read more)

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Methods used in the Paper


METHOD TYPE
ReLU
Activation Functions
Layer Normalization
Normalization
1x1 Convolution
Convolutions
Residual Connection
Skip Connections
Softmax
Output Functions
Global Context Block
Image Model Blocks
GCNet
Object Detection Models