Table 1.

Architectures of ResNet-50 and ResNet-101.

Layer name	Output size	ResNet-50	ResNet-101
conv1	112 × 112	7 × 7, 64
conv2_x	56 × 56	3 × 3 max pool
		$\left[\begin{array}{c}1\times 1,64\\ 3\times 3,64\\ 1\times 1,256\end{array}\right]$×3	$\left[\begin{array}{c}1\times 1,64\\ 3\times 3,64\\ 1\times 1,256\end{array}\right]$×3
conv3_x	28 × 28	$\left[\begin{array}{c}1\times 1,128\\ 3\times 3,128\\ 1\times 1,512\end{array}\right]$×4	$\left[\begin{array}{c}1\times 1,64\\ 3\times 3,64\\ 1\times 1,256\end{array}\right]$×4
conv4_x	14 × 14	$\left[\begin{array}{c}1\times 1,256\\ 3\times 3,256\\ 1\times 1,1024\end{array}\right]$×6	$\left[\begin{array}{c}1\times 1,256\\ 3\times 3,256\\ 1\times 1,1024\end{array}\right]$×23
conv4_x	7 × 7	$\left[\begin{array}{c}1\times 1,512\\ 3\times 3,512\\ 1\times 1,2048\end{array}\right]$×3	$\left[\begin{array}{c}1\times 1,512\\ 3\times 3,512\\ 1\times 1,2048\end{array}\right]$×3
avg_pool, fc1000, fc1000_softmax	1 × 1	Average pool, classification, softmax