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arXiv · 2501.05823

PersonaHOI: Effortlessly Improving Personalized Face with Human-Object Interaction Generation

Xinting Hu·Haoran Wang·Jan Eric Lenssen·Bernt Schiele
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Abstract

We introduce PersonaHOI, a training- and tuning-free framework that fuses a general StableDiffusion model with a personalized face diffusion (PFD) model to generate identity-consistent human-object interaction (HOI) images. While existing PFD models have advanced significantly, they often overemphasize facial features at the expense of full-body coherence, PersonaHOI introduces an additional StableDiffusion (SD) branch guided by HOI-oriented text inputs. By incorporating cross-attention constraints in the PFD branch and spatial merging at both latent and residual levels, PersonaHOI preserves personalized facial details while ensuring interactive non-facial regions. Experiments, validated by a novel interaction alignment metric, demonstrate the superior realism and scalability of PersonaHOI, establishing a new standard for practical personalized face with HOI generation. Our code will be available at https://github.com/JoyHuYY1412/PersonaHOI

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Xinting Hu, Haoran Wang, Jan Eric Lenssen, Bernt Schiele. 2025-01-10. PersonaHOI: Effortlessly Improving Personalized Face with Human-Object Interaction Generation. https://arxiv.org/abs/2501.05823

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