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Human-object interactions with articulated objects are common in everydaylife. Despite much progress in single-view 3D reconstruction, it is stillchallenging to infer an articulated 3D object model from an RGB video showing aperson manipulating the object. We canonicalize the task of articulated 3Dhuman-object interaction reconstruction from RGB video, and carry out asystematic benchmark of five families of methods for this task: 3D planeestimation, 3D cuboid estimation, CAD model fitting, implicit field fitting,and free-form mesh fitting. Our experiments show that all methods struggle toobtain high accuracy results even when provided ground truth information aboutthe observed objects. We identify key factors which make the task challengingand suggest directions for future work on this challenging 3D computer visiontask. Short video summary at https://www.youtube.com/watch?v=5tAlKBojZwc

Articulated 3D Human-Object Interactions from RGB Videos: An Empirical Analysis of Approaches and Challenges