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The study of hand-object interaction requires generating viable grasp poses for high-dimensional multi-finger models, often relying on analytic grasp synthesis which tends to produce brittle and unnatural results.
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Brahmbhatt, S., Tang, C., Twigg, C.D., Kemp, C.C., Hays, J.: Contactpose: A dataset of grasps with object contact and hand pose. In: ECCV (2020)
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2017
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2017
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Nakamura, Y.C., Troniak, D.M., Rodriguez, A., Mason, M.T., Pollard, N.S.: The complexities of grasping in the wild. In: International Conference on Humanoid Robotics (2017)
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Zhou, Y., Hauser, K.: 6dof grasp planning by optimizing a deep learning scoring function. In: RSS (2017)
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2020
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Taheri, O., Ghorbani, N., Black, M.J., Tzionas, D.: Grab: A dataset of whole-body human grasping of objects. In: ECCV (2020)
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2021
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Lakshmipathy, A., Bauer, D., Bauer, C., Pollard, N.S.: Contact transfer: A direct, user-driven method for human to robot transfer of grasps and manipulations. In: 2022 International Conference on Robotics and Automation (ICRA). pp. 6195–6201. IEEE (2022)
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