| --- |
| license: cc-by-4.0 |
| pretty_name: MLLM Visual Emotion |
| task_categories: |
| - image-classification |
| - visual-question-answering |
| language: |
| - en |
| tags: |
| - emotion-recognition |
| - facial-expression |
| - multimodal |
| - large-language-models |
| - benchmark |
| - visual-emotion-analysis |
| size_categories: |
| - 1K-10K |
| viewer: false |
| configs: |
| - config_name: default |
| data_files: [] |
| --- |
| |
| # MLLMVisualEmotion |
|
|
| > **Reading Human Emotion Through Machine Eyes** |
|
|
| This repository accompanies the study *"Reading Human Emotion Through Machine Eyes"* on visual emotion recognition by multimodal large language models (MLLMs). It contains the newly constructed **FaceEmotion** dataset, the preprocessed **Emotion6** dataset, outcome tables, source data underlying all figures, and the complete model outputs for all tasks across all scenarios. |
|
|
| ## Repository Structure |
|
|
| ``` |
| MLLMVisualEmotion/ |
| ├── datasets/ |
| │ ├── Emotion6/ |
| │ │ └── processed/ |
| │ │ ├── emotion_dataset.json |
| │ │ ├── images_multiple_choice_questions.json |
| │ │ ├── images_judgement_questions.json |
| │ │ ├── images_marked_multiple_choice_questions.json |
| │ │ ├── images_could_judgement_questions.json |
| │ │ ├── images_really_judgement_questions.json |
| │ │ ├── images_emotional_tendency_multiple_choice_questions.json |
| │ │ ├── images_emotional_tendency_judgement_questions.json |
| │ │ └── imgs/ |
| │ └── FaceEmotion/ |
| │ └── processed/ |
| │ ├── emotion_dataset.json |
| │ ├── images_multiple_choice_questions.json |
| │ ├── images_judgement_questions.json |
| │ ├── images_marked_multiple_choice_questions.json |
| │ ├── images_could_judgement_questions.json |
| │ ├── images_really_judgement_questions.json |
| │ ├── images_emotional_tendency_multiple_choice_questions.json |
| │ ├── images_emotional_tendency_judgement_questions.json |
| │ └── imgs/ |
| ├── model_outputs/ |
| │ ├── Undeterminable_results.json |
| │ ├── Gemini3p1Flash/ |
| │ ├── GPT4o/ |
| │ ├── GPT5/ |
| │ ├── InternVL2/ |
| │ ├── InternVL3/ |
| │ ├── LLaVA1p5/ |
| │ ├── LLaVA1p6/ |
| │ ├── Qwen2/ |
| │ ├── Qwen2p5/ |
| │ └── Qwen3/ |
| └── Source_Data.xlsx |
| ``` |
|
|
| ## Datasets |
|
|
| ### Emotion6 (Preprocessed) |
|
|
| The Emotion6 dataset is a widely used benchmark for visual emotion recognition, originally consisting of 1,980 images collected from Flickr. Each image is annotated with one of seven emotion categories (*Anger, Disgust, Fear, Joy, Neutral, Sadness, Surprise*) and an arousal value on a 1–9 scale. |
|
|
| - **`emotion_dataset.json`** — Image filenames, emotion labels, and arousal values. |
| - **`imgs/`** — The image files. |
| |
| ### FaceEmotion (Newly Constructed) |
| |
| FaceEmotion is a newly constructed dataset of 1,000 facial expression images, each annotated with one of seven emotion categories (*Anger, Disgust, Fear, Joy, Neutral, Sadness, Surprise*). |
| |
| - **`emotion_dataset.json`** — Image filenames and emotion labels. |
| - **`imgs/`** — The image files. |
|
|
| ### Task Input Files |
|
|
| For each dataset, the following JSON files contain the formatted prompts used as inputs to the MLLMs: |
|
|
| | File | Task Description | |
| |------|-----------------| |
| | `images_multiple_choice_questions.json` | Multi-class emotion selection (7-way classification) | |
| | `images_judgement_questions.json` | Binary emotion judgement (Yes/No per emotion category) | |
| | `images_marked_multiple_choice_questions.json` | Multi-class emotion selection with contextual cues | |
| | `images_could_judgement_questions.json` | Binary emotion judgement with "Could" contextual framing | |
| | `images_really_judgement_questions.json` | Binary emotion judgement with "really" contextual framing | |
| | `images_emotional_tendency_multiple_choice_questions.json` | Multi-class emotion selection with emotional tendency framing | |
| | `images_emotional_tendency_judgement_questions.json` | Binary emotion judgement with emotional tendency framing | |
|
|
| Each entry in these files contains: |
| - **Image identifier** and path |
| - **Ground-truth label** |
| - **Experiment setup** identifier |
| - **Query** (the full prompt sent to the model) |
| - **Answer** (the ground-truth answer) |
| - **Arousal** value (Emotion6 only) |
|
|
| ## Model Outputs |
|
|
| The `model_outputs/` directory contains the raw outputs from 10 MLLMs evaluated on all tasks: |
|
|
| | Model | Directory | |
| |-------|-----------| |
| | Gemini 3.1 Flash | `Gemini3p1Flash/` | |
| | GPT-4o | `GPT4o/` | |
| | GPT-5 | `GPT5/` | |
| | InternVL2 | `InternVL2/` | |
| | InternVL3 | `InternVL3/` | |
| | LLaVA 1.5 | `LLaVA1p5/` | |
| | LLaVA 1.6 | `LLaVA1p6/` | |
| | Qwen2-VL | `Qwen2/` | |
| | Qwen2.5-VL | `Qwen2p5/` | |
| | Qwen3-VL | `Qwen3/` | |
|
|
| Each model directory contains two subdirectories: |
| - **`Emotion6/`** — Results on the natural-scene Emotion6 dataset. |
| - **`FaceEmotion/`** — Results on the facial-expression FaceEmotion dataset. |
|
|
| Within each subdirectory, result files mirror the task input files: |
|
|
| | File | Task Description | |
| |------|-----------------| |
| | `images_multiple_choice_results.json` | Multi-class emotion selection results | |
| | `images_judgement_results.json` | Binary emotion judgement results | |
| | `images_marked_multiple_choice_results.json` | Multi-class selection with contextual cues results | |
| | `images_could_judgement_results.json` | Binary judgement with "Could" framing results | |
| | `images_really_judgement_results.json` | Binary judgement with "really" framing results | |
| | `images_emotional_tendency_multiple_choice_results.json` | Multi-class selection with emotional tendency results | |
| | `images_emotional_tendency_judgement_results.json` | Binary judgement with emotional tendency results | |
|
|
| Each result entry extends the input entry with: |
| - **`AI_answer`** — The model's predicted answer. |
| - **`accuracy`** — Binary accuracy score (1 = correct, 0 = incorrect). |
| - **`model_output`** — The full raw text output from the model. |
|
|
| ### Undeterminable Results |
|
|
| **`Undeterminable_results.json`** records, for each model and each scenario (Emotion6 / FaceEmotion), the count and frequency of "Undeterminable" responses in the multi-class emotion selection task that includes an "Undeterminable" option. |
| |
| ## Source Data |
| |
| **`Source_Data.xlsx`** contains the outcome tables and source data underlying all figures presented in the study. |
|
|
| ## License |
|
|
| This dataset is released under the [Creative Commons Attribution 4.0 International (CC BY 4.0)](https://creativecommons.org/licenses/by/4.0/) license. |
|
|
| ## Citation |
|
|
| If you use this dataset in your research, please cite the corresponding paper. |
|
|
| ## Contact |
|
|
| For questions or issues, please open a discussion on the Hugging Face repository. |
