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The intimate entanglement between objects affordances and human poses is oflarge interest, among others, for behavioural sciences, cognitive psychology,and Computer Vision communities. In recent years, the latter has developedseveral object-centric approaches: starting from items, learning pipelinessynthesizing human poses and dynamics in a realistic way, satisfying bothgeometrical and functional expectations. However, the inverse perspective issignificantly less explored: Can we infer 3D objects and their poses from humaninteractions alone? Our investigation follows this direction, showing that ageneric 3D human point cloud is enough to pop up an unobserved object, evenwhen the user is just imitating a functionality (e.g., looking through abinocular) without involving a tangible counterpart. We validate our methodqualitatively and quantitatively, with synthetic data and sequences acquiredfor the task, showing applicability for XR/VR. The code is available athttps://github.com/ptrvilya/object-popup.

Object pop-up: Can we infer 3D objects and their poses from human interactions alone?