\begin{table}[!h]
	\centering
	\scalebox{0.90}{
	\begin{tabular}{lccc}
		\toprule
		\bf{Model} & Backbone & $1$-shot & $5$-shot \\
		\midrule
		ProtoNet* \cite{Snell2017PrototypicalNF} & ResNet18& - & 62.02$\pm$0.70 \\
		SimpleShot* \cite{Wang2019SimpleShotRN} & ResNet18 & 48.56 & 65.63 \\
		MatchNet*  \cite{vinyals2016matching} &ResNet10& 36.61$\pm$0.53 & 55.23$\pm$0.83 \\
		NegMargin* \cite{liu2020negative} &ResNet18 & - & 69.30$\pm$0.70 \\
		MetaOptNet* \cite{Lee2019MetaLearningWD} &ResNet12 & 44.79$\pm$0.75 & 64.98$\pm$0.68 \\
		ASL \cite{afrasiyabi2020associative}   &ResNet18& 46.85$\pm$0.75 & 70.37$\pm$1.02 \\
		FRN \cite{wertheimer2021few}  &ResNet12& 54.11$\pm$0.19 & 77.09$\pm$0.15 \\
		\midrule
		Ours &ResNet12& \bf74.10$\pm$0.75 & \bf86.37$\pm$0.60 \\
		\bottomrule
	\end{tabular}
	}
	\caption{
		Performance comparison in the cross-domain setting: \textit{mini}ImageNet $\rightarrow$ CUB-200-2011 in the $5$-way $k$-shot scenario. ``*'' : denotes results reported by \cite{wertheimer2021few}.
	} 
	\label{tab:3}
\end{table}