Check out https://github.com/kenshohara/3D-ResNets-PyTorch 115
While this does not directly answer your question it nevertheless provides networks adapted from 2D architectures which are pretrained on temporal tasks and exhibit the conv3d system you speak of.
Utilizing one of the pretrained networks is likely easier then implementing your own LRCN. Furthermore, it seems like the results of these pretrained networks are quite good. (maybe better then LRCN?)