5 papers
From Tokens to Numbers: Continuous Number Modeling for SVG Generation
Michael Ogezi, Martin Bell, Freda Shi +1
For certain image generation tasks, vector graphics such as Scalable Vector Graphics (SVGs) offer clear benefits such as increased flexibility, size efficiency, and editing ease, b…
SpaRE: Enhancing Spatial Reasoning in Vision-Language Models with Synthetic Data
Michael Ogezi, Freda Shi
Vision-language models (VLMs) work well in tasks ranging from image captioning to visual question answering (VQA), yet they struggle with spatial reasoning, a key skill for underst…
Optimizing Negative Prompts for Enhanced Aesthetics and Fidelity in Text-To-Image Generation
Michael Ogezi, Ning Shi
In text-to-image generation, using negative prompts, which describe undesirable image characteristics, can significantly boost image quality. However, producing good negative promp…
UAlberta at SemEval-2023 Task 1: Context Augmentation and Translation for Multilingual Visual Word Sense Disambiguation
Michael Ogezi, Bradley Hauer, Talgat Omarov +2
We describe the systems of the University of Alberta team for the SemEval-2023 Visual Word Sense Disambiguation (V-WSD) Task. We present a novel algorithm that leverages glosses re…
Semantically-Prompted Language Models Improve Visual Descriptions
Michael Ogezi, Bradley Hauer, Grzegorz Kondrak
Language-vision models like CLIP have made significant strides in vision tasks, such as zero-shot image classification (ZSIC). However, generating specific and expressive visual de…