2 citations · 2 across the 5 of their papers we have counts for
6 papers
CognitionCapturerPro: Towards High-Fidelity Visual Decoding from EEG/MEG via Multi-modal Information and Asymmetric Alignment
Kaifan Zhang, Lihuo He, Junjie Ke +4
Visual stimuli reconstruction from EEG remains challenging due to fidelity loss and representation shift. We propose CognitionCapturerPro, an enhanced framework that integrates EEG…
YOLOA: Real-Time Affordance Detection via LLM Adapter
Yuqi Ji, Junjie Ke, Lihuo He +5
Affordance detection aims to jointly address the fundamental "what-where-how" challenge in embodied AI by understanding "what" an object is, "where" the object is located, and "how…
Shrinking the Teacher: An Adaptive Teaching Paradigm for Asymmetric EEG-Vision Alignment
Lukun Wu, Jie Li, Ziqi Ren +2
Decoding visual features from EEG signals is a central challenge in neuroscience, with cross-modal alignment as the dominant approach. We argue that the relationship between visual…
CognitionCapturer: Decoding Visual Stimuli From Human EEG Signal With Multimodal Information
Kaifan Zhang, Lihuo He, Xin Jiang +3
Electroencephalogram (EEG) signals have attracted significant attention from researchers due to their non-invasive nature and high temporal sensitivity in decoding visual stimuli.…
AI-Generated Image Quality Assessment Based on Task-Specific Prompt and Multi-Granularity Similarity
Jili Xia, Lihuo He, Fei Gao +3
Recently, AI-generated images (AIGIs) created by given prompts (initial prompts) have garnered widespread attention. Nevertheless, due to technical nonproficiency, they often suffe…
MsMorph: An Unsupervised pyramid learning network for brain image registration
Jiaofen Nan, Gaodeng Fan, Kaifan Zhang +3
In the field of medical image analysis, image registration is a crucial technique. Despite the numerous registration models that have been proposed, existing methods still fall sho…