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--- |
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license: mit |
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dataset_info: |
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features: |
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- name: id |
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dtype: string |
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- name: instructions |
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dtype: string |
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- name: answer |
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dtype: string |
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- name: image |
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dtype: image |
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splits: |
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- name: train |
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num_bytes: 243404574.5 |
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num_examples: 8956 |
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- name: validation |
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num_bytes: 25165334.5 |
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num_examples: 1116 |
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download_size: 196488037 |
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dataset_size: 268569909 |
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configs: |
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- config_name: default |
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data_files: |
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- split: train |
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path: data/train-* |
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- split: validation |
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path: data/validation-* |
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task_categories: |
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- question-answering |
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- summarization |
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language: |
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- en |
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tags: |
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- code |
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size_categories: |
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- 10K<n<100K |
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--- |
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# Emotion Dataset |
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## Dataset Description |
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### Dataset Summary |
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BoEM: A Multimodal VQA Dataset for Fine-Grained Facial Emotion Recognition. |
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This dataset contains facial expressions with corresponding emotion labels. Each image is labeled with emotions such as fear, happiness, sadness, etc., along with intensity information. |
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### Languages |
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The dataset annotations are in English. |
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## Dataset Structure |
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### Data Instances |
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Each instance in the dataset consists of: |
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- `id`: Unique identifier for the image |
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- `image`: The facial expression image |
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- `instructions`: The prompt/instruction given to annotate the image |
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- `answer`: The emotion label assigned to the image |
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### Data Fields |
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- `id`: String - Unique identifier for each sample |
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- `image`: Image - The facial expression image |
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- `instructions`: String - The prompt/instruction given to annotate the image |
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- `answer`: String - The emotion label/description |
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### Data Splits |
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The dataset is divided into training and validation splits. |
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## Dataset Creation |
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### Source Data |
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The dataset contains facial expressions collected for emotion recognition tasks. |
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### Annotations |
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The images are annotated with emotion labels and intensity information. |
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## Considerations for Using the Data |
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### Licensing Information |
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MIT |
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@misc{emotionbench2026submission, |
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title = {BoEM: A Multimodal VQA Dataset for Emotion Recognition}, |
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author = {Hoang Nam Dang, Lockheed Martin, Mei-Huei Tang}, |
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year = {2026}, |
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note = {Manuscript submitted to CVPR 2026}, |
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} |
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