This repository contains trained models reported in the paper "Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset" by Joao Carreira and Andrew Zisserman.
Tensorflow code is from Deepmind's Kinetics-I3D.
Pytorch code is from Kinetics-I3D
These models were pretrained on imagenet and kinetics (see original repo) for details).
You need to down load the checkpoint from the original repo
- default load the kinetics pre-trained model
- extract features in thumos14 validation and test dataset the extract way is segment the video at uniform interval.
| frames | interval | video fps |
|---|---|---|
| <=15000 | 24 | 30 |
| <=30000 | 48 | 30 |
| >30000 | 96 | 30 |
In order to reduce the redundancy in frames, we choose to subsample the video to 10fps. A clip includes 48 frames, we sample 16 frames and send to the I3D network to extract [1,1024] features
Feature is generated after Mix_5c and avg_pool layer:
input -> output:
rgb: [1, 16, 224, 224, 3] -> [1024,]
flow:[1, 16, 224, 224, 2] -> [1024,]