There are many hurdles that prevent the replication of existing work which hinders the development of new activity classification models. These hurdles include switching between multiple deep learning libraries and the development of boilerplate experimental pipelines. We present M-PACT to overcome existing issues by removing the need to develop boilerplate code which allows users to quickly prototype action classification models while leveraging existing state-of-the-art (SOTA) models...
Topics: actvity recognition, weights, c3d, i3d, tsn, resnet, lstm
Source: http://academictorrents.com/details/dcea7fa53925b31215bd8437d2f0805253d6b00f
