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--- |
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license: mit |
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pretty_name: L-Mind |
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size_categories: |
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- 10K<n<100K |
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task_categories: |
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- image-to-image |
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language: |
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- en |
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- zh |
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tags: |
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- eeg |
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- fnirs |
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- bci |
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- image-editing |
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- multimodal |
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configs: |
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- config_name: speech |
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data_files: |
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- split: train |
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path: train_speech.jsonl |
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- split: test |
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path: test_speech.jsonl |
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- config_name: legacy |
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data_files: |
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- split: train |
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path: train_0424.jsonl |
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- split: test |
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path: test_0424.jsonl |
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--- |
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# L-Mind: A Multimodal Dataset for Neural-Driven Image Editing |
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This dataset is part of the **NeurIPS 2025** paper: **"Neural-Driven Image Editing"**, which introduces **LoongX**, a hands-free image editing approach driven by multimodal neurophysiological signals. |
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## 📄 Overview |
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**L-Mind** is a large-scale multimodal dataset designed to bridge Brain-Computer Interfaces (BCIs) with generative AI. It enables research into accessible, intuitive image editing for individuals with limited motor control or language abilities. |
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- **Total Samples:** 23,928 image editing pairs |
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- **Participants:** 12 subjects (plus cross-subject evaluation data) |
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- **Task:** Instruction-based image editing viewed and conceived by users |
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## 🧠 Modalities |
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The dataset features synchronized recordings of: |
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1. **EEG** (Electroencephalography): Captures rapid neural dynamics (4 channels: Pz, Fp2, Fpz, Oz). |
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2. **fNIRS** (Functional Near-Infrared Spectroscopy): Measures hemodynamic responses (cognitive load/emotion). |
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3. **PPG** (Photoplethysmography): Monitors physiological state (heart rate/stress). |
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4. **Head Motion**: 6-axis IMU data tracking user movement. |
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5. **Speech**: Audio instructions provided by users. |
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6. **Visuals**: Source Image, Target Image, and Text Instruction. |
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## 🚀 Applications |
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This dataset supports the training of neural-driven generative models (like LoongX) that can interpret user intent directly from brain and physiological signals to perform: |
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- Background replacement |
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- Object manipulation |
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- Global stylistic changes |
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- Text editing |
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## 🔗 Resources |
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- **Project Website:** [https://loongx1.github.io](https://loongx1.github.io) |
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- **Paper:** [Neural-Driven Image Editing](https://arxiv.org/abs/2507.05397) |
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## 📚 Citation |
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If you use this dataset, please cite: |
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```bibtex |
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@inproceedings{zhouneural, |
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title={Neural-Driven Image Editing}, |
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author={Zhou, Pengfei and Xia, Jie and Peng, Xiaopeng and Zhao, Wangbo and Ye, Zilong and Li, Zekai and Yang, Suorong and Pan, Jiadong and Chen, Yuanxiang and Wang, Ziqiao and others}, |
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booktitle={The Thirty-ninth Annual Conference on Neural Information Processing Systems} |
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} |
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``` |
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