Transfer-learning for video classification: Video Swin Transformer on multiple domains. (arXiv:2210.09969v1 [cs.CV])

The computer vision community has seen a shift from convolutional-based to
pure transformer architectures for both image and video tasks. Training a
transformer from zero for these tasks usually requires a lot of data and
computational resources. Video Swin Transformer (VST) is a pure-transformer
model developed for video classification which achieves state-of-the-art
results in accuracy and efficiency on several datasets. In this paper, we aim
to understand if VST generalizes well enough to be used in an out-of-domain
setting. We …

arxiv classification swin transfer transformer video