UNIMO-G: Unified Image Generation through Multimodal Conditional Diffusion

no code implementations • 24 Jan 2024 • Wei Li, Xue Xu, Jiachen Liu, Xinyan Xiao

This paper presents UNIMO-G, a simple multimodal conditional diffusion framework that operates on multimodal prompts with interleaved textual and visual inputs, which demonstrates a unified ability for both text-driven and subject-driven image generation.

Conditional Image Generation Denoising +5

UPainting: Unified Text-to-Image Diffusion Generation with Cross-modal Guidance

no code implementations • 28 Oct 2022 • Wei Li, Xue Xu, Xinyan Xiao, Jiachen Liu, Hu Yang, Guohao Li, Zhanpeng Wang, Zhifan Feng, Qiaoqiao She, Yajuan Lyu, Hua Wu

Diffusion generative models have recently greatly improved the power of text-conditioned image generation.

Image Generation Image-text matching +2

Real-time Scene Text Detection Based on Global Level and Word Level Features

no code implementations • 10 Mar 2022 • Fuqiang Zhao, Jionghua Yu, Enjun Xing, Wenming Song, Xue Xu

Specifically, with a backbone of ResNet-50, we achieve an F-measure of 88. 6% on MSRA- TD500, 87. 9% on Total-Text, 89. 2% on ICDAR2015 and 87. 5% on CTW-1500.

Binarization Scene Text Detection +1

Interpretation of Electrocardiogram (ECG) Rhythm by Combined CNN and BiLSTM

no code implementations • IEEE Access ( Volume: 8) 2020 • Xue Xu, SOHYUN JEONG, Jianqiang Li

In this paper, we proposed a combined network of convolutional neural network (CNN) and Recurrent Neural Network (RNN), designed for the classification of ECG heart signals for diagnostic purpose.

Cloud Computing Specificity