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arXiv · 2501.12393

Towards Affordance-Aware Articulation Synthesis for Rigged Objects

Yu-Chu Yu·Chieh Hubert Lin·Hsin-Ying Lee·Chaoyang Wang·Yu-Chiang Frank Wang·Ming-Hsuan Yang
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Abstract

Rigged objects are commonly used in artist pipelines, as they can flexibly adapt to different scenes and postures. However, articulating the rigs into realistic affordance-aware postures (e.g., following the context, respecting the physics and the personalities of the object) remains time-consuming and heavily relies on human labor from experienced artists. In this paper, we tackle the novel problem and design A3Syn. With a given context, such as the environment mesh and a text prompt of the desired posture, A3Syn synthesizes articulation parameters for arbitrary and open-domain rigged objects obtained from the Internet. The task is incredibly challenging due to the lack of training data, and we do not make any topological assumptions about the open-domain rigs. We propose using 2D inpainting diffusion model and several control techniques to synthesize in-context affordance information. Then, we develop an efficient bone correspondence alignment using a combination of differentiable rendering and semantic correspondence. A3Syn has stable convergence, completes in minutes, and synthesizes plausible affordance on different combinations of in-the-wild object rigs and scenes.

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Yu-Chu Yu, Chieh Hubert Lin, Hsin-Ying Lee, Chaoyang Wang, Yu-Chiang Frank Wang, Ming-Hsuan Yang. 2025-01-21. Towards Affordance-Aware Articulation Synthesis for Rigged Objects. https://arxiv.org/abs/2501.12393

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