Search Results for author:
Found 14 papers, 6 papers with code
GR-2: A Generative Video-Language-Action Model with Web-Scale Knowledge for Robot Manipulation
We present GR-2, a state-of-the-art generalist robot agent for versatile and generalizable robot manipulation.
A Progressive Single-Modality to Multi-Modality Classification Framework for Alzheimer's Disease Sub-type Diagnosis
Second, we align features from modalities acquired in earlier low-cost stage(s) with later high-cost stage(s) to give accurate diagnosis without actual modality acquisition in later-stage(s) for saving cost.
Potential of Multimodal Large Language Models for Data Mining of Medical Images and Free-text Reports
Our experimental results demonstrated that Gemini-series models excelled in report generation and lesion detection but faces challenges in disease classification and anatomical localization.
IRASim: Learning Interactive Real-Robot Action Simulators
We hope that IRASim can serve as an effective and scalable approach to enhance robot learning in the real world.
TexVocab: Texture Vocabulary-conditioned Human Avatars
To adequately utilize the available image evidence in multi-view video-based avatar modeling, we propose TexVocab, a novel avatar representation that constructs a texture vocabulary and associates body poses with texture maps for animation.
CLIP in Medical Imaging: A Comprehensive Survey
With the aim of facilitating a deeper understanding of this promising direction, this survey offers an in-depth exploration of the CLIP paradigm within the domain of medical imaging, regarding both refined CLIP pre-training and CLIP-driven applications.
Vector Quantized Multi-modal Guidance for Alzheimer’s Disease Diagnosis Based on Feature Imputation
Magnetic Resonance Imaging (MRI) and positron emission tomography (PET) are the most used imaging modalities for Alzheimer’s disease (AD) diagnosis in clinics.
ChatRadio-Valuer: A Chat Large Language Model for Generalizable Radiology Report Generation Based on Multi-institution and Multi-system Data
Radiology report generation, as a key step in medical image analysis, is critical to the quantitative analysis of clinically informed decision-making levels.
Evaluating Large Language Models for Radiology Natural Language Processing
The rise of large language models (LLMs) has marked a pivotal shift in the field of natural language processing (NLP).
PoseVocab: Learning Joint-structured Pose Embeddings for Human Avatar Modeling
To this end, we present PoseVocab, a novel pose encoding method that encourages the network to discover the optimal pose embeddings for learning the dynamic human appearance.
Transformer-Based Multimodal Fusion for Early Diagnosis of Alzheimer's Disease Using Structural MRI And PET
To encourage effective information exchange between structural MRI (sMRI) and FDG-PET as used in our study for early AD diagnosis, we propose a novel transformer-based multimodal fusion framework.
DoctorGLM: Fine-tuning your Chinese Doctor is not a Herculean Task
The recent progress of large language models (LLMs), including ChatGPT and GPT-4, in comprehending and responding to human instructions has been remarkable.
3D Face Arbitrary Style Transfer
To solve this problem, we propose a novel method, namely Face-guided Dual Style Transfer (FDST).
Bounding Regression Errors in Data-driven Power Grid Steady-state Models
Results identify how the bounds decrease with additional power grid physical knowledge or more training data.
