% Subtable
\begin{table}[t!]
	\centering
	\begin{subtable}{.5\textwidth}
	%\centering
	\scalebox{0.90}{
	\begin{tabular}{lccc}
		\toprule
		Method & Backbone & $1-$shot & $5-$shot \\
		\midrule
		Cosine \cite{chen2019closer}  & ResNet34 & 68.00$\pm$0.83 & 84.50$\pm$0.51 \\
		MatchNet \cite{vinyals2016matching}  & ResNet12 & 71.87$\pm$0.85 & 85.08$\pm$0.57 \\
		NegMargin \cite{liu2020negative}  & ResNet18 & 72.66$\pm$0.85 & 89.40$\pm$0.43 \\
		S2M2 \cite{mangla2020charting}  & ResNet18 & 71.81$\pm$0.43 & 86.22$\pm$0.53 \\
		S2M2 \cite{mangla2020charting}  & ResNet34 & 72.92$\pm$0.83 & 86.55$\pm$0.51 \\
		FEAT* \cite{ye2020few}  & ResNet12 & 73.27$\pm$0.22 & 85.77$\pm$0.14 \\
		DeepEMD \cite{zhang2020deepemd}  & ResNet12 & 75.65$\pm$0.83 & 88.69$\pm$0.50 \\
		ProtoNet \cite{Snell2017PrototypicalNF} & ResNet12 & 66.09$\pm$0.92 & 82.50$\pm$0.58 \\
		RENet \cite{kang2021relational}  & ResNet12 & 79.49$\pm$0.44 & 91.11$\pm$0.24 \\
		SLK-MS \cite{ziko2021transductive} & ResNet18 & 81.88 & 88.55 \\
		EPNet \cite{rodriguez2020embedding} & ResNet12 & 82.85$\pm$0.81 & 91.32$\pm$0.41 \\
		FRN \cite{wertheimer2021few} & ResNet12 & \bf83.55$\pm$0.19 & \bf92.92$\pm$0.10 \\
		\midrule
		Ours   & ResNet12 & 82.95$\pm$0.67 & 90.80$\pm$0.51 \\
		\bottomrule
	\end{tabular}
	}
	\caption{\small Results on CUB-200-2011 dataset.}
	\end{subtable}
	
	\centering
	\begin{subtable}{.5\textwidth}
	%\centering
	\scalebox{0.92}{
	\begin{tabular}{lccc}
		\toprule
		Method & Backbone & $1-$shot & $5-$shot \\
		\midrule
		Cosine \cite{chen2019closer} & ResNet34 & 60.39$\pm$0.28 & 72.85$\pm$0.65 \\
		S2M2 \cite{mangla2020charting}  & ResNet18 & 63.66$\pm$0.17&76.07$\pm$0.19 \\
		S2M2 \cite{mangla2020charting}  & ResNet34 &  62.77$\pm$0.23&75.75$\pm$0.13 \\
		ProtoNet \cite{Snell2017PrototypicalNF} & ResNet12 & 72.20$\pm$0.70&83.50$\pm$0.50 \\
		MetaOptNet \cite{Lee2019MetaLearningWD} & ResNet12 &72.80$\pm$0.70& 85.00$\pm$0.50 \\
		Boosting \cite{gidaris2019boosting} & WRN28 & 73.60$\pm$0.30&86.00$\pm$0.20 \\
		RENet \cite{kang2021relational}  & ResNet12 & 74.51$\pm$0.46&86.60$\pm$0.32 \\
		\midrule
		Ours   & ResNet12 & \bf79.97$\pm$0.72 & \bf94.13$\pm$0.41 \\
		\bottomrule
	\end{tabular}
	}
	\caption{\small Results on CIFAR-FS dataset.}
	\end{subtable}
	\caption{
		Few-shot classification accuracy on CUB-200-2011 and CIFAR-FS in the $5$-way $k$-shot setting (mean accuracy in the $\pm95\%$ confidence interval). ``*'' : denotes results reproduced by \cite{kang2021relational}.
	}
	\label{tab:2}
	\vspace{-3mm}
\end{table}



