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The physical properties of an object, such as mass, significantly affect how we manipulate it with our hands.
The OpenCV Library
G. Bradski · 2000
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Physically based grasping control from example
Nancy S Pollard and Victor Brian Zordan · 2005
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Data-driven grasp synthesis using shape matching and task-based pruning
Ying Li, Jiaxin L Fu, and Nancy S Pollard · 2007
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Refining grasp affordance models by experience
Renaud Detry, Dirk Kraft, Anders Glent Buch, Norbert Krüger, and Justus Piater · 2010
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On the efficient computation of independent contact regions for force closure grasps
Robert Krug, Dimitar Dimitrov, Krzysztof Charusta, and Boyko Iliev · 2010
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Imitation learning of hand gestures and its evaluation for humanoid robots
Anand Thobbi and Weihua Sheng · 2010
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Contact-invariant optimization for hand manipulation
Igor Mordatch, Zoran Popović, and Emanuel Todorov · 2012
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Synthesis of detailed hand manipulations using contact sampling
Yuting Ye and C Karen Liu · 2012
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Generative adversarial nets
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2014
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Auto-encoding variational bayes
Diederik P Kingma and Max Welling · 2014
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TensorFlow: Large-scale machine learning on heterogeneous systems, 2015
Martín Abadi, Ashish Agarwal, Paul Barham, Eugene Brevdo, Zhifeng Chen, Craig Citro, Greg S. Corrado, Andy Davis, Jeffrey Dean, Matthieu Devin, Sanjay Ghemawat, Ian Goodfellow, Andrew Harp, Geoffrey Irving, Michael Isard, Yangqing Jia, Rafal Jozefowicz, Lukasz Kaiser, Manjunath Kudlur, Josh Levenberg, Dandelion Mané, Rajat Monga, Sherry Moore, Derek Murray, Chris Olah, Mike Schuster, Jonathon Shlens, Benoit Steiner, Ilya Sutskever, Kunal Talwar, Paul Tucker, Vincent Vanhoucke, Vijay Vasudevan, Fernanda Viégas, Oriol Vinyals, Pete Warden, Martin Wattenberg, Martin Wicke, Yuan Yu, and Xiaoqiang Zheng · 2015
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Fast and accurate deep network learning by exponential linear units (elus)
Djork-Arné Clevert, Thomas Unterthiner, and Sepp Hochreiter · 2015
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Deep unsupervised learning using nonequilibrium thermodynamics
Jascha Sohl-Dickstein, Eric Weiss, Niru Maheswaranathan, and Surya Ganguli · 2015
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Learning structured output representation using deep conditional generative models
Kihyuk Sohn, Honglak Lee, and Xinchen Yan · 2015
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Hand-object interaction detection with fully convolutional networks
Matthias Schroder and Helge Ritter · 2017
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Contactdb: Analyzing and predicting grasp contact via thermal imaging
Samarth Brahmbhatt, Cusuh Ham, Charles C Kemp, and James Hays · 2019
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Mediapipe: A framework for perceiving and processing reality
Camillo Lugaresi, Jiuqiang Tang, Hadon Nash, Chris McClanahan, Esha Uboweja, Michael Hays, Fan Zhang, Chuo-Ling Chang, Ming Yong, Juhyun Lee, et al · 2019
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Real-time pose and shape reconstruction of two interacting hands with a single depth camera
Franziska Mueller, Micah Davis, Florian Bernard, Oleksandr Sotnychenko, Mickeal Verschoor, Miguel A Otaduy, Dan Casas, and Christian Theobalt · 2019
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H+ o: Unified egocentric recognition of 3d hand-object poses and interactions
Bugra Tekin, Federica Bogo, and Marc Pollefeys · 2019
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Vaegan: A collaborative filtering framework based on adversarial variational autoencoders
Xianwen Yu, Xiaoning Zhang, Yang Cao, and Min Xia · 2019
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Semi-supervised 3d hand-object poses estimation with interactions in time
Shaowei Liu, Hanwen Jiang, Jiarui Xu, Sifei Liu, and Xiaolong Wang · 2021
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Manipnet: Neural manipulation synthesis with a hand-object spatial representation
He Zhang, Yuting Ye, Takaaki Shiratori, and Taku Komura · 2021
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D-grasp: Physically plausible dynamic grasp synthesis for hand-object interactions
Sammy Christen, Muhammed Kocabas, Emre Aksan, Jemin Hwangbo, Jie Song, and Otmar Hilliges · 2022
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Physical interaction: Reconstructing hand-object interactions with physics
Haoyu Hu, Xinyu Yi, Hao Zhang, Jun-Hai Yong, and Feng Xu · 2022
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High-resolution image synthesis with latent diffusion models
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer · 2022
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On the continuity of rotation representations in neural networks
Yi Zhou, Connelly Barnes, Jingwan Lu, Jimei Yang, and Hao Li · 2019
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Ganhand: Predicting human grasp affordances in multi-object scenes
Enric Corona, Albert Pumarola, Guillem Alenya, Francesc Moreno-Noguer, and Grégory Rogez · 2020
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Action2motion: Conditioned generation of 3d human motions
Chuan Guo, Xinxin Zuo, Sen Wang, Shihao Zou, Qingyao Sun, Annan Deng, Minglun Gong, and Li Cheng · 2020
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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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Grasping field: Learning implicit representations for human grasps
Korrawe Karunratanakul, Jinlong Yang, Yan Zhang, Michael J Black, Krikamol Muandet, and Siyu Tang · 2020
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GRAB: A dataset of whole-body human grasping of objects
Omid Taheri, Nima Ghorbani, Michael J. Black, and Dimitrios Tzionas · 2020
Cited alongside, same era.
Rgb2hands: real-time tracking of 3d hand interactions from monocular rgb video
Jiayi Wang, Franziska Mueller, Florian Bernard, Suzanne Sorli, Oleksandr Sotnychenko, Neng Qian, Miguel A Otaduy, Dan Casas, and Christian Theobalt · 2020
Cited alongside, same era.
Chitwan Saharia, William Chan, Saurabh Saxena, Lala Li, Jay Whang, Emily Denton, Seyed Kamyar Seyed Ghasemipour, Burcu Karagol Ayan, S Sara Mahdavi, Rapha Gontijo Lopes, et al · 2022
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Goal: Generating 4d whole-body motion for hand-object grasping
Omid Taheri, Vasileios Choutas, Michael J Black, and Dimitrios Tzionas · 2022
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Motiondiffuse: Text-driven human motion generation with diffusion model
Mingyuan Zhang, Zhongang Cai, Liang Pan, Fangzhou Hong, Xinying Guo, Lei Yang, and Ziwei Liu · 2022
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Toch: Spatio-temporal object correspondence to hand for motion refinement
Keyang Zhou, Bharat Bhatnagar, Jan Eric Lenssen, and Gerard Pons-Moll · 2022
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Mofusion: A framework for denoising-diffusion-based motion synthesis
Rishabh Dabral, Muhammad Hamza Mughal, Vladislav Golyanik, and Christian Theobalt · 2023
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Imos: Intent-driven full-body motion synthesis for human-object interactions
Anindita Ghosh, Rishabh Dabral, Vladislav Golyanik, Christian Theobalt, and Philipp Slusallek · 2023
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Dreamfusion: Text-to-3d using 2d diffusion
Ben Poole, Ajay Jain, Jonathan T Barron, and Ben Mildenhall · 2023
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Human motion diffusion model
Guy Tevet, Sigal Raab, Brian Gordon, Yonatan Shafir, Daniel Cohen-Or, and Amit H Bermano · 2023
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Physdiff: Physics-guided human motion diffusion model
Ye Yuan, Jiaming Song, Umar Iqbal, Arash Vahdat, and Jan Kautz · 2023
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Cams: Canonicalized manipulation spaces for category-level functional hand-object manipulation synthesis
Juntian Zheng, Qingyuan Zheng, Lixing Fang, Yun Liu, and Li Yi · 2023
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