SAGA: Stochastic Whole-Body Grasping with Contact
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Abstract (arXiv)
The synthesis of human grasping has numerous applications including AR/VR, video games and robotics. While methods have been proposed to generate realistic hand-object interaction for object grasping and manipulation, these typically only consider interacting hand alone. Our goal is to synthesize whole-body grasping motions. Starting from an arbitrary initial pose, we aim to generate diverse and natural whole-body human motions to approach and grasp a target object in 3D space. This task is challenging as it requires modeling both whole-body dynamics and dexterous finger movements. To this end, we propose SAGA (StochAstic whole-body Grasping with contAct), a framework which consists of two key components: (a) Static whole-body grasping pose generation. Specifically, we propose a multi-task generative model, to jointly learn static whole-body grasping poses and human-object contacts. (b) Grasping motion infilling. Given an initial pose and the generated whole-body grasping pose as the start and end of the motion respectively, we design a novel contact-aware generative motion infilling module to generate a diverse set of grasp-oriented motions. We demonstrate the effectiveness of our method, which is a novel generative framework to synthesize realistic and expressive whole-body motions that approach and grasp randomly placed unseen objects. Code and models are available at https://jiahaoplus.github.io/SAGA/saga.html.
Key facts. Cited by 91 papers in the map (data through 14 Oct 2026). Builds on 39 of its 68 references that are in the map. First posted on arXiv 19 Dec 2021.
Builds on
39 of 68 references.
References · 39
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- 2020Long-term Human Motion Prediction with Scene Contextcited by 192
- 2020DLow: Diversifying Latent Flows for Diverse Human Motion Predictioncited by 185
- 2021Character Controllers Using Motion VAEscited by 184
- 2020Grasping Field: Learning Implicit Representations for Human Graspscited by 179
- 2017HP-GAN: Probabilistic 3D human motion prediction via GANcited by 176
- 2021Hand-Object Contact Consistency Reasoning for Human Grasps Generationcited by 160
- 2019ContactDB: Analyzing and Predicting Grasp Contact via Thermal Imagingcited by 147
- 2021ContactOpt: Optimizing Contact to Improve Graspscited by 139
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- 2018MT-VAE: Learning Motion Transformations to Generate Multimodal Human Dynamicscited by 86
- 2020Convolutional Autoencoders for Human Motion Infillingcited by 73
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- 2018Action-Agnostic Human Pose Forecastingcited by 56
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Citing papers per year: 2022: 5; 2023: 25; 2024: 31; 2025: 19; 2026: 11.
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- 2024THOR: Text to Human-Object Interaction Diffusion via Relation Intervention17 Mar 2024
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