SoftwareApplication
name: Code underlying the publication: "Video BagNet: short temporal receptive fields increase robustness in long-term action recognition"
description: Code underlying the publication: "Video BagNet: short temporal receptive fields increase robustness in long-term action recognition"
description: Previous work on long-term video action recognition relies on deep 3D-convolutional models that have a large temporal receptive field (RF). We argue that these models are not always the best choice for temporal modeling in videos. A large temporal receptive field allows the model to encode the exact sub-action order of a video, which causes a performance decrease when testing videos have a different sub-action order. In this work, we investigate whether we can improve the model robustness to the sub-action order by shrinking the temporal receptive field of action recognition models. For this, we design Video BagNet, a variant of the 3D ResNet-50 model with the temporal receptive field size limited to 1, 9, 17 or 33 frames. We analyze Video Bag-Net on synthetic and real-world video datasets and experimentally compare models with varying temporal receptive fields. We find that short receptive fields are robust to sub-action order changes, while larger temporal receptive fields are sensitive to the sub-action order. In this repository, we provide our code, including the implementation of Video Bag-Net.
code repository: https://data.4tu.nl/v3/datasets/9f4b04e3-81a5-4d03-a0da-ccb8d7d7d311.git
author: Person
  given name: Ombretta
  family name: Strafforello
  name: Ombretta Strafforello
author: Person
  given name: Xin
  family name: Liu
  name: Xin Liu
author: https://orcid.org/0000-0002-6913-0482
author: https://orcid.org/0000-0002-9954-0685
keywords: Action recognition
keywords: Temporal receptive field
keywords: 3D-CNN
keywords: BagNet
keywords: computer vision
programming language: Markdown
programming language: Other
programming language: Python
programming language: XML
license:
  creative work: creativeWork
    name: CC0-1.0
reference publication: iccvw60793.2023.00023

https://orcid.org/0000-0002-6913-0482
type: Person
given name: Jan
family name: van Gemert
name: Jan van Gemert

https://orcid.org/0000-0002-9954-0685
type: Person
given name: Klamer
family name: Schutte
name: Klamer Schutte

iccvw60793.2023.00023
type: ScholarlyArticle
name: Video BagNet: short temporal receptive fields increase robustness in long-term action recognition
pagination: 159-166
url: https://doi.org/10.1109%2Ficcvw60793.2023.00023