activity
20232026
most citedPushing the Limits of 3D Shape Generation at Scale

4 citations · 4 across the 8 of their papers we have counts for

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cs.CV2026

fMRI2Face: A Full-HD fMRI-Video Dataset and Geometry-Guided Neural Decoding Framework for Dynamic Human Face Reconstruction

Jingyang Huo, Xiangru Huang, Chentao Shen +6

Reconstructing dynamic human faces from brain activity provides a powerful way to study how the mind perceives identity, expression, and facial motion. However, progress in fMRI-ba…

cs.CV2026

The Pictorial Cortex: Zero-Shot Cross-Subject fMRI-to-Image Reconstruction via Compositional Latent Modeling

Jingyang Huo, Yikai Wang, Yanwei Fu +1

Decoding visual experiences from human brain activity remains a central challenge at the intersection of neuroscience, neuroimaging, and artificial intelligence. A critical obstacl…

cs.CV2025

DecoFuse: Decomposing and Fusing the "What", "Where", and "How" for Brain-Inspired fMRI-to-Video Decoding

Chong Li, Jingyang Huo, Weikang Gong +3

Decoding visual experiences from brain activity is a significant challenge. Existing fMRI-to-video methods often focus on semantic content while overlooking spatial and motion info…

cs.CV2024

NeuroPictor: Refining fMRI-to-Image Reconstruction via Multi-individual Pretraining and Multi-level Modulation

Jingyang Huo, Yikai Wang, Xuelin Qian +4

Recent fMRI-to-image approaches mainly focused on associating fMRI signals with specific conditions of pre-trained diffusion models. These approaches, while producing high-quality…

cs.CV2024

Intelligent Director: An Automatic Framework for Dynamic Visual Composition using ChatGPT

Sixiao Zheng, Jingyang Huo, Yu Wang +1

With the rise of short video platforms represented by TikTok, the trend of users expressing their creativity through photos and videos has increased dramatically. However, ordinary…

cs.CV2023

fMRI-PTE: A Large-scale fMRI Pretrained Transformer Encoder for Multi-Subject Brain Activity Decoding

Xuelin Qian, Yun Wang, Jingyang Huo +2

The exploration of brain activity and its decoding from fMRI data has been a longstanding pursuit, driven by its potential applications in brain-computer interfaces, medical diagno…