Brainwaves to Pixels: Notes on EEG-Based Image Reconstruction
About
Hi~😉 I’m Ignisavium, a student passionate about EEG-based image reconstruction. These notes are part of my ongoing effort to organize and share knowledge on this fascinating topic. Feel free to explore my work or contribute on GitHub: @ignisavium .
Key Topics Covered
- 🧠Introduction: Basics of EEG and image reconstruction techniques. (EEG itself; Diffusion Model Intro
- 📘Papers & Methods: Insights from seminal studies and algorithms.
- 🤔Reflections : Limitations and future directions in the field.
In recent years, Diffusion Model has gradually become the mainstream of generative models due to its excellent performance and convenient integration features. Here we mainly focus on the EEG to Image reconstruction method based on diffusion.
Paper Compilation
This is a summary of cutting-edge work in recent years.
EEG-based Image Reconstruction
| 时间 | 标题 |
|---|---|
| 2210 | Decoding Visual Neural Representations by Multimodal Learning of Brain-Visual-Linguistic Features |
| 2211 | High-resolution image reconstruction with latent diffusion models from human brain activity |
| 2211 | Seeing beyond the brain：Conditional diffusion model with sparse masked modeling for vision decoding |
| 2212 | NeuroGAN：image reconstruction from EEG signals via an attention-based GAN |
| 2302 | EEG2IMAGE：Image Reconstruction from EEG Brain Signals |
| 2303 | DCA：A dual conditional autoencoder framework for the reconstruction from EEG into image |
| 2303 | High-resolution image reconstruction with latent diffusion models from human brain activity |
| 2303 | MindDiffuser：Controlled Image Reconstruction from Human Brain Activity with Semantic and Structural Diffusion |
| 2303 | [Apdx]High-resolution image reconstruction with latent diffusion models from human brain activity |
| 2305 | Reconstructing the Mind's Eye：fMRI-to-Image with Contrastive Learning and Diffusion Priors |
| 2306 | DreamDiffusion：Generating High-Quality Images from Brain EEG Signals |
| 2306 | Improving visual image reconstruction from human brain activity using latent diffusion models via multiple decoded inputs |
| 2308 | Decoding Natural Images from EEG for Object Recognition |
| 2308 | Seeing through the Brain：Image Reconstruction of Visual Perception from Human Brain Signals |
| 2308 | UniBrain：Unify Image Reconstruction and Captioning All in One Diffusion Model from Human Brain Activity |
| 2309 | Decoding visual brain representations from electroencephalography through Knowledge Distillation and latent diffusion models |
| 2309 | DM-RE2I：A framework based on diffusion model for the reconstruction from EEG to image |
| 2310 | DM-RE2I：A framework based on diffusion model for the reconstruction from EEG to image |
| 2310 | Learning Robust Deep Visual Representations from EEG Brain Recordings |
| 2310 | Learning_Robust_Deep_Visual_Representations_From_EEG_Brain_Recordings_WACV_2024_paper |
| 2312 | BrainVis：Exploring the Bridge between Brain and Visual Signals via Image Reconstruction |
| 2401 | Visual image reconstruction based on EEG signals using a generative adversarial and deep fuzzy neural network |
| 2402 | MambaMIR：An Arbitrary-Masked Mamba for Joint Medical Image Reconstruction and Uncertainty Estimation |
| 2402 | Next Generation Imaging in Consumer Technology for ERP Detection-Based EEG Cross-Subject Visual Object Recognition |
| 2403 | Reconstructing Visual Stimulus Representation From EEG Signals Based on Deep Visual Representation Model |
| 2403 | Semantics-Guided Hierarchical Feature Encoding Generative Adversarial Network for fMRI2img |
| 2403 | Visual Decoding and Reconstruction via EEG Embeddings with Guided Diffusion |
| 2403 | Visual Decoding and Reconstruction via EEG |
| 2404 | A New Framework Combining Diffusion Models and the Convolution Classifier for Generating Images from EEG Signals |
| 2404 | Neuro-Vision to Language：Enhancing Brain Recording-based Visual Reconstruction and Language Interaction |
| 2405 | A New Framework Combining Diffusion Models and the Convolution Classifier for Generating Images from EEG Signals |
| 2406 | Autoregressive Model Beats Diffusion：Llama for Scalable Image Generation |
| 2406 | Evaluating the Feasibility of Visual Imagery for an EEG-Based Brain–Computer Interface |
| 2406 | Evaluating the Feasibility of Visual Imagery for an EEG-Based Brain–Computer Interfacepfd |
| 2406 | Mind's Eye：Image Recognition by EEG via Multimodal Similarity-Keeping Contrastive Learning |
| 2407 | EidetiCom：A Cross-modal Brain-Computer Semantic Communication Paradigm for Decoding Visual Perception |
| 2407 | Image classification and reconstruction from low-density EEG |
| 2407 | MB2C：Multimodal Bidirectional Cycle Consistency for Learning Robust Visual Neural Representations |
| 2409 | BrainDecoder：Style-Based Visual Decoding of EEG Signals |
| 2410 | NECOMIMI：Neural-Cognitive Multimodal EEG-informed Image Generation with Diffusion Models |
| 2410 | Research on Brain Visual Image Signal Recognition Method Based on Deep Neural Network |
| 2412 | CognitionCapturer：Decoding Visual Stimuli From Human EEG Signal With Multimodal Information |
| 2505 | Deep Learning for EEG-Based Visual Classification and Reconstruction：Panorama, Trends, Challenges and Opportunities |
| 2505 | [Survey] Visual Image Reconstruction from Brain Activity via Latent Representation |
| 2507 | [Survey] Interpretable EEG-to-Image Generation with Semantic Prompts |
Diffusion Model
| 时间 | 标题 |
|---|---|
| Tutorial on Diffusion Models for Imaging and Vision | |
| [DDPM]Denoising Diffusion Probabilistic Models | |
| [Score Matching]Score-Based Generative Modeling through SDEs | |
| [Stable Diffusion]High-Resolution Image Synthesis with Latent Diffusion Models | |
| 2105 | Diffusion Models Beat GANs on Image Synthesis |
| 2211 | Versatile diffusion：Text, images and variations all in one diffusion model |
| 2308 | IP-Adapter：Text Compatible Image Prompt Adapter for Text-to-Image Diffusion Models |
| 2310 | Language Model Beats Diffusion -- Tokenizer is Key to Visual Generation |
| 2406 | Autoregressive Model Beats Diffusion：Llama for Scalable Image Generation |