Search Results for author:
Found 5 papers, 1 papers with code
NeuroPictor: Refining fMRI-to-Image Reconstruction via Multi-individual Pretraining and Multi-level Modulation
Recent fMRI-to-image approaches mainly focused on associating fMRI signals with specific conditions of pre-trained diffusion models.
Intelligent Director: An Automatic Framework for Dynamic Visual Composition using ChatGPT
We propose an Intelligent Director framework, utilizing LENS to generate descriptions for images and video frames and combining ChatGPT to generate coherent captions while recommending appropriate music names.
fMRI-PTE: A Large-scale fMRI Pretrained Transformer Encoder for Multi-Subject Brain Activity Decoding
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 diagnostics, and virtual reality.
Pushing the Limits of 3D Shape Generation at Scale
Through the adaptation of the Auto-Regressive model and the utilization of large language models, we have developed a remarkable model with an astounding 3. 6 billion trainable parameters, establishing it as the largest 3D shape generation model to date, named Argus-3D.
GeoVLN: Learning Geometry-Enhanced Visual Representation with Slot Attention for Vision-and-Language Navigation
Technically, we introduce a two-stage module that combine local slot attention and CLIP model to produce geometry-enhanced representation from such input.
