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Hands are dexterous and highly versatile manipulators that are central to how humans interact with objects and their environment.
Retargetting motion to new characters
Michael Gleicher · 1998
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Ying Li, Jiaxin L. Fu, and Nancy S. Pollard · 2007
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Edmond S. L. Ho, Taku Komura, and Chiew-Lan Tai · 2010
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Igor Mordatch, Zoran Popovic, and Emanuel Todorov · 2012
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Rami Ali Al-Asqhar, Taku Komura, and Myung Geol Choi · 2013
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Robust realtime physics-based motion control for human grasping
Wenping Zhao, Jianjie Zhang, Jianyuan Min, and Jinxiang Chai · 2013
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Data-driven grasp synthesis—a survey
Jeannette Bohg, Antonio Morales, Tamim Asfour, and Danica Kragic · 2014
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SMPL: A Skinned Multi-Person Linear Model
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The KIT whole-body human motion database
Christian Mandery, Ömer Terlemez, Martin Do, Nikolaus Vahrenkamp, and Tamim Asfour · 2015
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Precision: Precomputing environment semantics for contact-rich character animation
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Terrain-adaptive locomotion skills using deep reinforcement learning
Xue Bin Peng, Glen Berseth, and Michiel Van de Panne · 2016
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Capturing hands in action using discriminative salient points and physics simulation
Dimitrios Tzionas, Luca Ballan, Abhilash Srikantha, Pablo Aponte, Marc Pollefeys, and Juergen Gall · 2016
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Xue Bin Peng, Glen Berseth, Kangkang Yin, and Michiel Van De Panne · 2017
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Kevin Bergamin, Simon Clavet, Daniel Holden, and James Richard Forbes · 2019
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Grasping Field: Learning implicit representations for human grasps
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GRAB: A dataset of whole-body human grasping of objects
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A system for general in-hand object re-orientation
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ContactOpt: Optimizing contact to improve grasps
Patrick Grady, Chengcheng Tang, Christopher D. Twigg, Minh Vo, Samarth Brahmbhatt, and Charles C. Kemp · 2021
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ContactDB: Analyzing and predicting grasp contact via thermal imaging
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On the continuity of rotation representations in neural networks
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Stochastic scene-aware motion prediction
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Hand-object contact consistency reasoning for human grasps generation
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A skeleton-driven neural occupancy representation for articulated hands
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ManipNet: Neural manipulation synthesis with a hand-object spatial representation
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Behave: Dataset and method for tracking human object interactions
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D-Grasp: Physically plausible dynamic grasp synthesis for hand-object interactions
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InterCap: Joint markerless 3D tracking of humans and objects in interaction
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Toch: Spatio-temporal object correspondence to hand for motion refinement
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