Connecting Dreams with Visual Brainstorming Instruction

TL;DR

This paper introduces DreamConnect, a novel framework that uses multimodal diffusion techniques to translate brain signals into visual imagery, enabling more accurate dream visualization.

Contribution

It presents a new dual-stream diffusion approach with asynchronous strategies for interfacing with and visualizing human dreams from brain signals.

Findings

High fidelity in dream imagery synthesis

Effective manipulation of brain signals using diffusion models

Framework demonstrates accurate dream visualization

Abstract

Recent breakthroughs in understanding the human brain have revealed its impressive ability to efficiently process and interpret human thoughts, opening up possibilities for intervening in brain signals. In this paper, we aim to develop a straightforward framework that uses other modalities, such as natural language, to translate the original dreamland. We present DreamConnect, employing a dual-stream diffusion framework to manipulate visually stimulated brain signals. By integrating an asynchronous diffusion strategy, our framework establishes an effective interface with human dreams, progressively refining their final imagery synthesis. Through extensive experiments, we demonstrate the method ability to accurately instruct human brain signals with high fidelity. Our project will be publicly available on https://github.com/Sys-Nexus/DreamConnect