---
license: cc-by-nc-nd-4.0
task_categories:
- video-classification
- video-text-to-text
tags:
- video
- Facial Recognition
- Computer Vision
- Machine learning
- Emotion Recognition
size_categories:
- 1K<n<10K
---
# Video Dataset of Various Emotions for Recognition Tasks

Dataset comprises **1,000+** videos featuring **11** facial emotions and **15** inner emotions expressed by individuals from diverse backgrounds, including various races, genders, and ages. It is designed for **emotion recognition** research, focusing on **emotion detection** and emotion **classification** tasks.

By utilizing this dataset, researchers can explore advanced **emotion analysis** techniques and develop robust recognition models that can accurately identify and classify **facial expressions** and **emotional categories**.  - **[Get the data](https://unidata.pro/datasets/video-emotion-recognition-dataset/?utm_source=huggingface&utm_medium=referral&utm_campaign=video-emotion-recognition-dataset)**

The dataset includes a wide range of emotional expressions, allowing for comprehensive studies in emotion predictions and expression recognition.

# 💵 Buy the Dataset: This is a limited preview of the data. To access the full dataset, please contact us at [https://unidata.pro](https://unidata.pro/datasets/video-emotion-recognition-dataset/?utm_source=huggingface&utm_medium=referral&utm_campaign=video-emotion-recognition-dataset) to discuss your requirements and pricing options.

## Metadata for the dataset
![](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F22059654%2Faf0c2d80d660c8d38184a9ff28a094b3%2FFrame%201%20(6).png?generation=1741771741312300&alt=media)
Variables in .csv files:
- id: Unique identifier for each video
- inner_emotion: The inner emotion expressed in the video
- facial_emotion: The facial emotion displayed in the video
- transcript: Text transcription of the video's content
- video: Link to the original video
- text: Link to the transcription

The dataset contains videos that capture a variety of facial expressions and emotions, including both positive and negative emotions. Each video is annotated with detailed information about the emotions displayed, enabling researchers to conduct in-depth analyses and comparisons across different emotion categories.

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