UbRV2A

Introduction

This is a Pytorch implementation of the model described in our paper:

Uncertainty-boosted Robust Video Activity Anticipation.

Dependencies

• Pytorch >= 1.0.1
• Cuda 9.0.176
• Cudnn 7.4.2
• Python 3.6.8

Data

EPIC-Kitchens-55 dataset

For the raw data of the EPIC-Kitchens dataset, please refer to https://github.com/epic-kitchens/download-scripts to download.

For the three modality features (rgb, flow, obj), please refer to https://github.com/fpv-iplab/rulstm to download.

EPIC-Kitchens-100 dataset

For the raw data of the EPIC-Kitchens dataset, please refer to https://github.com/epic-kitchens/download-scripts to download.

For the three modality features (rgb, flow, obj), please refer to https://github.com/fpv-iplab/rulstm to download.

EGTEA Gaze+ dataset

For the raw data of the EGTEA Gaze+ dataset, please refer to http://cbs.ic.gatech.edu/fpv/ to download.

For the extracted features, please refer to https://github.com/fpv-iplab/rulstm to download.

MECCANO dataset

For the raw data or extracted features of the MECCANO dataset, please refer to https://iplab.dmi.unict.it/MECCANO/ to download.

Train for Epic-Kitchen dataset

Validation for Epic-Kitchen dataset

Concat

If you have any problem with our code, feel free to contact

• qizb@hit.edu.cn