Action Recognition

Dataset UCF101 HMDB51 Kinetics

HMDB51 51 classes 7,000 clips

Kinetics 400 classes 300,000 clips

Architectures 3D Convnet 2D convnet → LSTM

3D Convnet Uses 3d kernel to interpret temporal data Is slower to train as it

2D Convnet → LSTM Can use image recongnition 2D convnet as a starting point to speed training Can be very deep due to using LSTM

Python, Tensorflow, Caffe, Examples Comfortable with Python Have used Tensorflow Need to finish installing Caffe Coding examples. (https://github.com/yjxiong/temporal-segment-networks) HMDB51