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Found 5 papers, 3 papers with code
DeeDSR: Towards Real-World Image Super-Resolution via Degradation-Aware Stable Diffusion
In the second stage, we integrate a degradation-aware module into a simplified ControlNet, enabling flexible adaptation to various degradations based on the learned representations.
GPT4Vis: What Can GPT-4 Do for Zero-shot Visual Recognition?
Our study centers on the evaluation of GPT-4's linguistic and visual capabilities in zero-shot visual recognition tasks: Firstly, we explore the potential of its generated rich textual descriptions across various categories to enhance recognition performance without any training.
MARIS: Referring Image Segmentation via Mutual-Aware Attention Features
Referring image segmentation (RIS) aims to segment a particular region based on a language expression prompt.
RT-SRTS: Angle-Agnostic Real-Time Simultaneous 3D Reconstruction and Tumor Segmentation from Single X-Ray Projection
In this study, a novel imaging method RT-SRTS is proposed which integrates 3D imaging and tumor segmentation into one network based on multi-task learning (MTL) and achieves real-time simultaneous 3D reconstruction and tumor segmentation from a single X-ray projection at any angle.
Flexible Alignment Super-Resolution Network for Multi-Contrast MRI
To tackle this problem, we propose the Flexible Alignment Super-Resolution Network (FASR-Net) for multi-contrast MRI Super-Resolution.
