[
    {
        "id": "osp-14945",
        "type": "article-journal",
        "title": "MAMHOI: Factorizing Scene-Aware Human-Object Interaction through Affordances",
        "author": [
            {
                "family": "Lei",
                "given": "Mingyuan"
            },
            {
                "family": "Sung",
                "given": "Yoonchang"
            },
            {
                "family": "Cham",
                "given": "Tat-Jen"
            }
        ],
        "URL": "https://omanscience.com/en/articles/mamhoi-factorizing-scene-aware-human-object-interaction-through-affordances",
        "language": "en",
        "issued": {
            "date-parts": [
                [
                    2026
                ]
            ]
        },
        "abstract": "Generating realistic human-object interactions (HOI) in complex 3D scenes requires two complementary capabilities: reasoning about interaction feasibility in the environment and synthesizing realistic human-object motion. However, supervision for these capabilities is rarely available jointly at scale. Human-scene datasets provide rich information about environment-aware motion, while human-object datasets capture detailed interaction dynamics, yet paired human-object-scene data remain scarce. We present MAMHOI, an affordance-mediated factorization for scene-aware human-object interaction generation. MAMHOI factorizes scene-aware HOI generation through an explicit motion-affordance interface between scene understanding and motion synthesis: a scene-conditioned model first predicts where and how an interaction can be feasibly executed, and an affordance-conditioned HOI model then generates the corresponding human-object motion. This factorization allows scene understanding and interaction dynamics to be learned from complementary sources of supervision without requiring paired human-object-scene data. Experiments in complex indoor environments show that MAMHOI reduces object--scene penetration while better preserving human--object interaction quality, yielding more realistic and physically feasible scene-aware interactions. Project page: https://leimingyuan.github.io/MAMHOI-project-page/"
    }
]