Yes, if X is reshaped to something like [64,1,672,672], you would again need to arrive at a shape of [64,n_inputs] ie [64, 224] so that it can be fed into the RNN.

Reshape it from [64, 3, 224, 224] to [64, 150528], apply a feed-forward layer to get the desired size for the basic_rnn layer.
Apply 2 or 3 Convolutional layers and bring them to the desired shape.

The 2nd approach will learn some spatial features as well, due to the Conv layers.