activity
20202026
most citedRobust Multimodal Image Registration Using Deep Recurrent Reinforcement Learning

34 citations · 69 across the 28 of their papers we have counts for

collaborators

28 papers

cs.CV2026

Evidence-Based Actor-Verifier Reasoning for Echocardiographic Agents

Peng Huang, Yiming Wang, Yineng Chen +9

Echocardiography plays an important role in the screening and diagnosis of cardiovascular diseases. However, automated intelligent analysis of echocardiographic data remains challe…

cs.CV2025

DAGLFNet: Deep Feature Attention Guided Global and Local Feature Fusion for Pseudo-Image Point Cloud Segmentation

Chuang Chen, Yi Lin, Bo Wang +3

Environmental perception systems are crucial for high-precision mapping and autonomous navigation, with LiDAR serving as a core sensor providing accurate 3D point cloud data. Effic…

cs.CV2025

RLMiniStyler: Light-weight RL Style Agent for Arbitrary Sequential Neural Style Generation

Jing Hu, Chengming Feng, Shu Hu +4

Arbitrary style transfer aims to apply the style of any given artistic image to another content image. Still, existing deep learning-based methods often require significant computa…

cs.CV2025

Real-Time Animatable 2DGS-Avatars with Detail Enhancement from Monocular Videos

Xia Yuan, Hai Yuan, Wenyi Ge +3

High-quality, animatable 3D human avatar reconstruction from monocular videos offers significant potential for reducing reliance on complex hardware, making it highly practical for…

eess.IV2025

Diffusion-empowered AutoPrompt MedSAM

Peng Huang, Shu Hu, Bo Peng +5

MedSAM, a medical foundation model derived from the SAM architecture, has demonstrated notable success across diverse medical domains. However, its clinical application faces two m…

cs.CL2025★ 3 cited

LLM-MedQA: Enhancing Medical Question Answering through Case Studies in Large Language Models

Hang Yang, Hao Chen, Hui Guo +6

Accurate and efficient question-answering systems are essential for delivering high-quality patient care in the medical field. While Large Language Models (LLMs) have made remarkab…