Full-Body Articulated Human-Object Interaction
Nan Jiang, Tengyu Liu, Zhexuan Cao, Jieming Cui, Zhiyuan Zhang, Yixin Chen, He Wang, Yixin Zhu, Siyuan Huang
摘要
Fine-grained capture of 3D Human-Object Interactions (HOIs) enhances human activity comprehension and supports various downstream visual tasks. However, previous models often assume that humans interact with rigid objects using only a few body parts, constraining their applicability. In this paper, we address the intricate challenge of Full-Body Articulated Human-Object Interaction (f-AHOI), where complete human bodies interact with articulated objects having interconnected movable joints. We introduce CHAIRS, an extensive motion-captured f-AHOI dataset comprising 17.3 hours of diverse interactions involving 46 participants and 81 articulated as well as rigid sittable objects. The CHAIRS provides 3D meshes of both humans and articulated objects throughout the interactive sequences, offering realistic and physically plausible full-body interactions. We demonstrate the utility of CHAIRS through object pose estimation. Leveraging the geometric relationships inherent in HOI, we propose a pioneering model that employs human pose estimation to address articulated object pose and shape estimation within whole-body interactions. Given an image and an estimated human pose, our model reconstructs the object’s pose and shape, refining the reconstruction based on a learned interaction prior. Across two evaluation scenarios, our model significantly outperforms baseline methods. Additionally, we showcase the significance of CHAIRS in a downstream task involving human pose generation conditioned on interacting with articulated objects. We anticipate that the availability of CHAIRS will advance the community’s understanding of finer-grained interactions.
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引用它的顶会 Paper34
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- The Quest for Generalizable Motion Generation: Data, Model, and EvaluationJing Lin, Ruisi Wang, Junzhe Lu, Ziqi Huang 等ICLR 2026 · 被引用 23 次
- Exo2Ego: Exocentric Knowledge Guided MLLM for Egocentric Video UnderstandingHaoyu Zhang, Qiaohui Chu, Meng Liu, Haoxiang Shi 等AAAI 2026 · 被引用 17 次
- GEARS: Local Geometry-Aware Hand-Object Interaction SynthesisKeyang Zhou, Bharat Lal Bhatnagar, Jan Eric Lenssen, Gerard Pons-MollCVPR 2024 · 被引用 9 次
- I'M HOI: Inertia-Aware Monocular Capture of 3D Human-Object InteractionsChengfeng Zhao, Juze Zhang, Jiashen Du, Ziwei Shan 等CVPR 2024 · 被引用 9 次
它引用的顶会 Paper26
- Pix2Pose: Pixel-Wise Coordinate Regression of Objects for 6D Pose EstimationKiru Park, Timothy Patten, Markus VinczeICCV 2019 · 被引用 527 次
- PARE: Part Attention Regressor for 3D Human Body EstimationMuhammed Kocabas, Chun-Hao P. Huang, Otmar Hilliges, Michael J. BlackICCV 2021 · 被引用 509 次
- Resolving 3D Human Pose Ambiguities With 3D Scene ConstraintsMohamed Hassan, Vasileios Choutas, Dimitrios Tzionas, Michael J. BlackICCV 2019 · 被引用 384 次
- Stochastic Scene-Aware Motion PredictionMohamed Hassan, Duygu Ceylan, Ruben Villegas, Jun Saito 等ICCV 2021 · 被引用 240 次
- Mining the Benefits of Two-stage and One-stage HOI DetectionAixi Zhang, Yue Liao, Si Liu, Miao Lu 等NeurIPS 2021 · 被引用 218 次
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