13 papers
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…
MemLearner: Learning to Query Context memory for Video World Models
Jiwen Yu, Jianxiong Gao, Jianhong Bai +7
Video World Models are interactive video generation models that predict future world states based on user actions and history video frames. A critical challenge in video world mode…
What Semantics Survive the Connector? Diagnosing VLM-to-DiT Alignment in Video Editing
Hangyu Lin, Chao Wen, Chengming Xu +4
Flow matching based video generative models have been increasingly relying on prepended Vision-Language Models (VLMs) to handle complex, instruction-based video editing. The prevai…
-WM: A Unified Video-Action World Model for Robotic Manipulation
Pengfei Zhou, Shengcong Chen, Di Chen +17
Robotic manipulation requires models that generate executable actions while anticipating and evaluating their future consequences before physical execution. We present -World…
Bridging Brain and Semantics: A Hierarchical Framework for Semantically Enhanced fMRI-to-Video Reconstruction
Yujie Wei, Chenglong Ma, Jianxiong Gao +6
Reconstructing dynamic visual experiences as videos from functional magnetic resonance imaging (fMRI) is pivotal for advancing the understanding of neural processes. However, curre…
Modeling Spatiotemporal Neural Frames for High Resolution Brain Dynamic
Wanying Qu, Jianxiong Gao, Wei Wang +1
Capturing dynamic spatiotemporal neural activity is essential for understanding large-scale brain mechanisms. Functional magnetic resonance imaging (fMRI) provides high-resolution…