PIDNet

PIDNet: A Real-time Semantic Segmentation Network Inspired from PID Controller

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This repository contain implementation of all three versions of PIDNet in Tensorflow/Keras.

Overview

An overview of the basic architecture of our proposed Proportional-Integral-Derivative Network (PIDNet).

P, I and D branches are responsiable for detail preservation, context embedding and boundary detection, respectively.

Detailed Implementation

Instantiation of the PIDNet for semantic segmentation.

For operation, "OP, N, C" means operation OP with stride of N and the No. output channel is C; Output: output size given input size of 1024; mxRB: m residual basic blocks; 2xRBB: 2 residual bottleneck blocks; OP₁\OP₂: OP₁ is used for PIDNet-L while OP₁ is applied in PIDNet-M and PIDNet-S. (m,n,C) are scheduled to be (2,3,32), (2,3,64) and (3,4,64) for PIDNet-S, PIDNet-M and PIDNet-L, respectively.

Dependies:
Tensorflow 2.3 or later

Licensed under MIT License