发布时间：2022-11-10 18:30
- we propose a two-stream ConvNet architecture which incorporates spatial and temporal networks
- demonstrate that a ConvNet trained on multi-frame dense optical flow is able to achieve very good performance in spite of limited training data.
- show that multitask learning, applied to two different action classification datasets, can be used to increase the amount of training data and improve the performance on both.