ResNet

Residual Network — a CNN architecture that uses skip connections (residual connections) to enable training of very deep networks (50–152+ layers) by alleviating the vanishing gradient problem. ResNet-18 and ResNet-50 are standard visual encoders in robot learning, providing a good balance of representational power and computational cost for real-time perception.