  We present a simple approach which can turn a ViT encoder into an efficient
video model, which can seamlessly work with both image and video inputs. By
sparsely sampling the inputs, the model is able to do training and inference
from both inputs. The model is easily scalable and can be adapted to
large-scale pre-trained ViTs without requiring full finetuning. The model
achieves SOTA results and the code will be open-sourced.
