2 citations · 6 across the 8 of their papers we have counts for
9 papers
MindVoice: Reconstructing Intelligible Speech from Non-invasive Neural Signals with Pretrained Priors
Guangyin Bao, Taiping Zeng, Jianfeng Feng +1
Reconstructing continuous speech from non-invasive neural recordings is a fundamental problem for probing human auditory perception and building safe, scalable speech brain-compute…
MindSimulator: Exploring Brain Concept Localization via Synthetic FMRI
Guangyin Bao, Qi Zhang, Zixuan Gong +2
Concept-selective regions within the human cerebral cortex exhibit significant activation in response to specific visual stimuli associated with particular concepts. Precisely loca…
Efficient Diffusion Models: A Survey
Hui Shen, Jingxuan Zhang, Boning Xiong +11
Diffusion models have emerged as powerful generative models capable of producing high-quality contents such as images, videos, and audio, demonstrating their potential to revolutio…
NeuroClips: Towards High-fidelity and Smooth fMRI-to-Video Reconstruction
Zixuan Gong, Guangyin Bao, Qi Zhang +9
Reconstruction of static visual stimuli from non-invasion brain activity fMRI achieves great success, owning to advanced deep learning models such as CLIP and Stable Diffusion. How…
FedMinds: Privacy-Preserving Personalized Brain Visual Decoding
Guangyin Bao, Duoqian Miao
Exploring the mysteries of the human brain is a long-term research topic in neuroscience. With the help of deep learning, decoding visual information from human brain activity fMRI…
Wills Aligner: Multi-Subject Collaborative Brain Visual Decoding
Guangyin Bao, Qi Zhang, Zixuan Gong +6
Decoding visual information from human brain activity has seen remarkable advancements in recent research. However, the diversity in cortical parcellation and fMRI patterns across…
MindTuner: Cross-Subject Visual Decoding with Visual Fingerprint and Semantic Correction
Zixuan Gong, Qi Zhang, Guangyin Bao +4
Decoding natural visual scenes from brain activity has flourished, with extensive research in single-subject tasks and, however, less in cross-subject tasks. Reconstructing high-qu…
Multimodal Federated Learning with Missing Modality via Prototype Mask and Contrast
Guangyin Bao, Qi Zhang, Duoqian Miao +5
In real-world scenarios, multimodal federated learning often faces the practical challenge of intricate modality missing, which poses constraints on building federated frameworks a…
Lite-Mind: Towards Efficient and Robust Brain Representation Network
Zixuan Gong, Qi Zhang, Guangyin Bao +5
The limited data availability and the low signal-to-noise ratio of fMRI signals lead to the challenging task of fMRI-to-image retrieval. State-of-the-art MindEye remarkably improve…