# ViT-ReT: Vision and Recurrent Transformer Neural Networks for Human Activity Recognition in Videos

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/vit-ret-vision-and-recurrent-transformer-neural-networks-for-human-activity/

## Facts

| Field | Value |
| --- | --- |
| Author Names | James Wensel,Hayat Ullah,Arslan Munir |
| Citations | 82 |
| DOI | 10.1109/access.2023.3293813 |
| Fields | Computer Science |
| Open Access | true |
| OA Status | gold |
| OA URL | https://ieeexplore.ieee.org/ielx7/6287639/6514899/10177697.pdf |
| OpenAlex ID | https://openalex.org/W4383751689 |
| Type | article |
| Year | 2023 |

## Paper authors

- [Hayat Ullah](https://scholariq.org/researchers/hayat-ullah/)

## Paper journal

- [IEEE Access](https://scholariq.org/journals/ieee-access/)

## Paper primary topic

- [Human Pose and Action Recognition](https://scholariq.org/topics/human-pose-and-action-recognition/)

## Paper topics

- [Human Pose and Action Recognition](https://scholariq.org/topics/human-pose-and-action-recognition/)
- [Anomaly Detection Techniques and Applications](https://scholariq.org/topics/anomaly-detection-techniques-and-applications/)
- [Context-Aware Activity Recognition Systems](https://scholariq.org/topics/context-aware-activity-recognition-systems/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.