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Found 5 papers, 0 papers with code
Empowering Backbone Models for Visual Text Generation with Input Granularity Control and Glyph-Aware Training
Diffusion-based text-to-image models have demonstrated impressive achievements in diversity and aesthetics but struggle to generate images with legible visual texts.
UNIMO-G: Unified Image Generation through Multimodal Conditional Diffusion
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.
UPainting: Unified Text-to-Image Diffusion Generation with Cross-modal Guidance
Diffusion generative models have recently greatly improved the power of text-conditioned image generation.
Real-time Scene Text Detection Based on Global Level and Word Level Features
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.
Interpretation of Electrocardiogram (ECG) Rhythm by Combined CNN and BiLSTM
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.
