# Video samples for the HKO-7 benchmark

This folder includes the video samples for algorithms tested in the paper.

2D-offline: 2D CNN model tested in the offline setting
2D-online: 2D CNN model tested in the online setting
3D-offline: 3D CNN model tested in the offline setting
3D-online: 3D CNN model tested in the online setting
ConvGRU-offline: ConvGRU model tested in the offline setting
ConvGRU-nobal: ConvGRU model trained without balanced loss and tested in the offline setting
ConvGRU-online: ConvGRU model tested in the online setting
Last-Frame: The simple baseline which always predict the last observed frame
ROVER-linear: The ROVER algorithm that uses optical flow to extrapolate the last frame
ROVER-non-linear: Variant of the ROVER algorithm, which first non-linearly transforms the input frame before calculating the optical flow
TrajGRU-offline: TrajGRU model tested in the offline setting
TrajGRU-online: TrajGRU model tested in the online setting


IMPORTANT!

We have not clipped the out-of-boundary pixels when generating the videos, so the predictions will go out-of-bound (as in the generated videos of the 2D and 3D CNNs). These loss will not be counted in training and testing.