5 citations · 10 across the 4 of their papers we have counts for
5 papers
Barycentric Guidance: Turning Foundation Image Editors into Continuous Affective Controllers
Harvey Mannering, Zhiwu Huang, Adam Prügel-Bennett
Emotions are expressed on a continuum and are naturally described in the valence-arousal (VA) space. Existing VA-based image editors are typically training-based and domain-specifi…
A Foundational EDM2-Based Generative Model for High-Resolution Synthetic Fetal Ultrasound Imaging from Open Datasets
Harvey Mannering, Yilin Zhang, Ziao Liu +3
Prenatal ultrasound imaging is key for assessing fetal health, but AI progress is limited by scarce, privacy-restricted, and hard-to-annotate datasets. We propose a high-resolution…
Noise-Level Diffusion Guidance: Well Begun is Half Done
Harvey Mannering, Zhiwu Huang, Adam Prugel-Bennett
Diffusion models have achieved state-of-the-art image generation. However, the random Gaussian noise used to start the diffusion process influences the final output, causing variat…
Analysing Gender Bias in Text-to-Image Models using Object Detection
Harvey Mannering
This work presents a novel strategy to measure bias in text-to-image models. Using paired prompts that specify gender and vaguely reference an object (e.g. "a man/woman holding an…
Towards Realistic Ultrasound Fetal Brain Imaging Synthesis
Michelle Iskandar, Harvey Mannering, Zhanxiang Sun +4
Prenatal ultrasound imaging is the first-choice modality to assess fetal health. Medical image datasets for AI and ML methods must be diverse (i.e. diagnoses, diseases, pathologies…