ForceHOSI: Force-Aware Human–Object–Scene Interaction Generation

Human–object–scene interaction generation requires more than moving an object to a target while avoiding collisions: the human posture must also reflect the physical demands of the interaction. Changing an object's weight or resistance can require different postural responses even when its geometry and the task remain unchanged. We present PhysHOSI, a force-aware framework that generates scene-conditioned interactions with load- and resistance-dependent human motion. Our method models postural adaptation as a continuous response field along a force coordinate. Action, interaction type, and force jointly modulate the field's temporal weights through a tensor-conditioned low-rank parameterization. A task-preserving composition module retains support motion and refines manipulation without suppressing the learned pose response. To support training and evaluation, we construct FORCE-Scene by grounding recorded force-annotated interactions in 3D scenes, checking ground support and penetration, and forming strategy-consistent response pairs. Experiments demonstrate state-of-the-art performance on the evaluated force-aware interaction benchmark. Under the paired reconstruction protocol, PhysHOSI achieves better force-response ordering, more accurate object positioning at the task goal, and higher task success than the task baseline. Additional obstacle demonstrations illustrate how different physical demands can be associated with different ways of completing the same task.