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Understanding how we grasp objects with our hands has important applications in areas like robotics and mixed reality.
Patterns of static prehension in normal hands
Noriko Kamakura, Michiko Matsuo, Harumi Ishii, Fumiko Mitsuboshi, and Yoriko Miura · 1980
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Robotic grasping and contact: A review
Antonio Bicchi and Vijay Kumar · 2000
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Image quality assessment: from error visibility to structural similarity
Zhou Wang, Alan C Bovik, Hamid R Sheikh, and Eero P Simoncelli · 2004
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A sensor fusion approach for recognizing continuous human grasping sequences using hidden markov models
Keni Bernardin, Koichi Ogawara, Katsushi Ikeuchi, and Ruediger Dillmann · 2005
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The neuroscience of grasping
Umberto Castiello · 2005
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Vision-based hand pose estimation: A review
Ali Erol, George Bebis, Mircea Nicolescu, Richard D Boyle, and Xander Twombly · 2007
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Matplotlib: A 2d graphics environment
J. D. Hunter · 2007
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An investigation of grasp type and frequency in daily household and machine shop tasks
Joshua Z Zheng, Sara De La Rosa, and Aaron M Dollar · 2011
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Motion capture of hands in action using discriminative salient points
Luca Ballan, Aparna Taneja, Jürgen Gall, Luc Van Gool, and Marc Pollefeys · 2012
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1 € filter: a simple speed-based low-pass filter for noisy input in interactive systems
Géry Casiez, Nicolas Roussel, and Daniel Vogel · 2012
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Data-driven grasp synthesis—a survey
Jeannette Bohg, Antonio Morales, Tamim Asfour, and Danica Kragic · 2013
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Interactive markerless articulated hand motion tracking using rgb and depth data
Srinath Sridhar, Antti Oulasvirta, and Christian Theobalt · 2013
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Adam: A method for stochastic optimization
Diederik P. Kingma and Jimmy Ba · 2014
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The yale human grasping dataset: Grasp, object, and task data in household and machine shop environments
Ian M Bullock, Thomas Feix, and Aaron M Dollar · 2015
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Understanding everyday hands in action from rgb-d images
Grégory Rogez, James S Supancic, and Deva Ramanan · 2015
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Every Thing We Touch: A 24-hour Inventory of Our Lives
Paula Zuccotti · 2015
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Perceptual losses for real-time style transfer and super-resolution
Justin Johnson, Alexandre Alahi, and Li Fei-Fei · 2016
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Structure-from-motion revisited
Johannes Lutz Schönberger and Jan-Michael Frahm · 2016
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Pixelwise view selection for unstructured multi-view stereo
Johannes Lutz Schönberger, Enliang Zheng, Marc Pollefeys, and Jan-Michael Frahm · 2016
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Real-time joint tracking of a hand manipulating an object from rgb-d input
Srinath Sridhar, Franziska Mueller, Michael Zollhöfer, Dan Casas, Antti Oulasvirta, and Christian Theobalt · 2016
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Real-time hand tracking under occlusion from an egocentric rgb-d sensor
Franziska Mueller, Dushyant Mehta, Oleksandr Sotnychenko, Srinath Sridhar, Dan Casas, and Christian Theobalt · 2017
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Hand-object contact force estimation from markerless visual tracking
Tu-Hoa Pham, Nikolaos Kyriazis, Antonis A Argyros, and Abderrahmane Kheddar · 2017
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Embodied hands: Modeling and capturing hands and bodies together
Javier Romero, Dimitrios Tzionas, and Michael J. Black · 2017
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Hand keypoint detection in single images using multiview bootstrapping
Tomas Simon, Hanbyul Joo, Iain Matthews, and Yaser Sheikh · 2017
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First-person hand action benchmark with rgb-d videos and 3d hand pose annotations
Guillermo Garcia-Hernando, Shanxin Yuan, Seungryul Baek, and Tae-Kyun Kim · 2018
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Total capture: A 3d deformation model for tracking faces, hands, and bodies
Hanbyul Joo, Tomas Simon, and Yaser Sheikh · 2018
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Ganerated hands for real-time 3d hand tracking from monocular rgb
Franziska Mueller, Florian Bernard, Oleksandr Sotnychenko, Dushyant Mehta, Srinath Sridhar, Dan Casas, and Christian Theobalt · 2018
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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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Learning implicit fields for generative shape modeling
Zhiqin Chen and Hao Zhang · 2019
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PyTorch Lightning, 2019
William Falcon and The PyTorch Lightning team · 2019
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Learning joint reconstruction of hands and manipulated objects
Yana Hasson, Gül Varol, Dimitrios Tzionas, Igor Kalevatykh, Michael J Black, Ivan Laptev, and Cordelia Schmid · 2019
Volume rendering of neural implicit surfaces
Lior Yariv, Jiatao Gu, Yoni Kasten, and Yaron Lipman · 2021
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Plenoxels: Radiance fields without neural networks
Alex Yu, Sara Fridovich-Keil, Matthew Tancik, Qinhong Chen, Benjamin Recht, and Angjoo Kanazawa · 2021
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Tensorf: Tensorial radiance fields
Anpei Chen, Zexiang Xu, Andreas Geiger, Jingyi Yu, and Hao Su · 2022
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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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Lisa: Learning implicit shape and appearance of hands
Enric Corona, Tomas Hodan, Minh Vo, Francesc Moreno-Noguer, Chris Sweeney, Richard Newcombe, and Lingni Ma · 2022
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Neural volumes: Learning dynamic renderable volumes from images
Stephen Lombardi, Tomas Simon, Jason Saragih, Gabriel Schwartz, Andreas Lehrmann, and Yaser Sheikh · 2019
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Occupancy networks: Learning 3d reconstruction in function space
Lars Mescheder, Michael Oechsle, Michael Niemeyer, Sebastian Nowozin, and Andreas Geiger · 2019
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Deepsdf: Learning continuous signed distance functions for shape representation
Jeong Joon Park, Peter Florence, Julian Straub, Richard Newcombe, and Steven Lovegrove · 2019
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Scene representation networks: Continuous 3d-structure-aware neural scene representations
Vincent Sitzmann, Michael Zollhoefer, and Gordon Wetzstein · 2019
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Freihand: A dataset for markerless capture of hand pose and shape from single rgb images
Christian Zimmermann, Duygu Ceylan, Jimei Yang, Bryan Russell, Max Argus, and Thomas Brox · 2019
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Contactpose: A dataset of grasps with object contact and hand pose
Samarth Brahmbhatt, Chengcheng Tang, Christopher D Twigg, Charles C Kemp, and James Hays · 2020
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Actionnet: A multimodal dataset for human activities using wearable sensors in a kitchen environment
Joseph DelPreto, Chao Liu, Yiyue Luo, Michael Foshey, Yunzhu Li, Antonio Torralba, Wojciech Matusik, and Daniela Rus · 2022
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Alphapose: Whole-body regional multi-person pose estimation and tracking in real-time
Hao-Shu Fang, Jiefeng Li, Hongyang Tang, Chao Xu, Haoyi Zhu, Yuliang Xiu, Yong-Lu Li, and Cewu Lu · 2022
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Keypoint transformer: Solving joint identification in challenging hands and object interactions for accurate 3d pose estimation
Shreyas Hampali, Sayan Deb Sarkar, Mahdi Rad, and Vincent Lepetit · 2022
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Harp: Personalized hand reconstruction from a monocular rgb video
Korrawe Karunratanakul, Sergey Prokudin, Otmar Hilliges, and Siyu Tang · 2022
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Hoi4d: A 4d egocentric dataset for category-level human-object interaction
Yunze Liu, Yun Liu, Che Jiang, Kangbo Lyu, Weikang Wan, Hao Shen, Boqiang Liang, Zhoujie Fu, He Wang, and Li Yi · 2022
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Instant neural graphics primitives with a multiresolution hash encoding
Thomas Müller, Alex Evans, Christoph Schied, and Alexander Keller · 2022
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Grasp’d: Differentiable contact-rich grasp synthesis for multi-fingered hands
Dylan Turpin, Liquan Wang, Eric Heiden, Yun-Chun Chen, Miles Macklin, Stavros Tsogkas, Sven Dickinson, and Animesh Garg · 2022
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HumanNeRF: Free-viewpoint rendering of moving people from monocular video
Chung-Yi Weng, Brian Curless, Pratul P. Srinivasan, Jonathan T. Barron, and Ira Kemelmacher-Shlizerman · 2022
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Neural fields in visual computing and beyond
Yiheng Xie, Towaki Takikawa, Shunsuke Saito, Or Litany, Shiqin Yan, Numair Khan, Federico Tombari, James Tompkin, Vincent Sitzmann, and Srinath Sridhar · 2022
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Fast-snarf: A fast deformer for articulated neural fields
Xu Chen, Tianjian Jiang, Jie Song, Max Rietmann, Andreas Geiger, Michael J Black, and Otmar Hilliges · 2023
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ARCTIC: A dataset for dexterous bimanual hand-object manipulation
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K-planes: Explicit radiance fields in space, time, and appearance
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3d gaussian splatting for real-time radiance field rendering
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Dynamic 3d gaussians: Tracking by persistent dynamic view synthesis
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Livehand: Real-time and photorealistic neural hand rendering
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Mixed neural voxels for fast multi-view video synthesis
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4d gaussian splatting for real-time dynamic scene rendering
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Nerf-ds: Neural radiance fields for dynamic specular objects
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Artigrasp: Physically plausible synthesis of bi-manual dexterous grasping and articulation
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