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Various heuristic objectives for modeling hand-object interaction have been proposed in past work.
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2015
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2015
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J. Romero, D. Tzionas, and M. J. Black, “Embodied hands: Modeling and capturing hands and bodies together,”
2017
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C. Zimmermann and T. Brox, “Learning to estimate 3d hand pose from single rgb images,” in
2017
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F. Mueller, D. Mehta, O. Sotnychenko, S. Sridhar, D. Casas, and C. Theobalt, “Real-time hand tracking under occlusion from an egocentric rgb-d sensor,” in
2017
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G. Garcia-Hernando, S. Yuan, S. Baek, and T.-K. Kim, “First-person hand action benchmark with rgb-d videos and 3d hand pose annotations,” in
2018
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2018
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Y. Xiang, T. Schmidt, V. Narayanan, and D. Fox, “Posecnn: A convolutional neural network for 6d object pose estimation in cluttered scenes,” in
2018
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Y. Cai, L. Ge, J. Cai, and J. Yuan, “Weakly-supervised 3d hand pose estimation from monocular rgb images,” in
2018
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L. Ge, Y. Cai, J. Weng, and J. Yuan, “Hand pointnet: 3d hand pose estimation using point sets,” in
2018
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F. Mueller, F. Bernard, O. Sotnychenko, D. Mehta, S. Sridhar, D. Casas, and C. Theobalt, “Ganerated hands for real-time 3d hand tracking from monocular rgb,” in
2018
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A. Spurr, J. Song, S. Park, and O. Hilliges, “Cross-modal deep variational hand pose estimation,” in
2018
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S. Yuan, G. Garcia-Hernando, B. Stenger, G. Moon, J. Chang, K. Lee, P. Molchanov, J. Kautz, S. Honari, L. Ge, J. Yuan, X. Chen, G. Wang, F. Yang, K. Akiyama, Y. Wu, Q. Wan, M. Madadi, S. Escalera, S. Li, D. Lee, I. Oikonomidis, A. Argyros, and T. Kim, “Depth-based 3d hand pose estimation: From current achievements to future goals,” in
2018
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P. Panteleris, I. Oikonomidis, and A. Argyros, “Using a single rgb frame for real time 3d hand pose estimation in the wild,” in
2018
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G. Garcia-Hernando, S. Yuan, S. Baek, and T.-K. Kim, “First-person hand action benchmark with rgb-d videos and 3d hand pose annotations,” in
2018
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Y. Hasson, G. Varol, D. Tzionas, I. Kalevatykh, M. J. Black, I. Laptev, and C. Schmid, “Learning joint reconstruction of hands and manipulated objects,” in
2019
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G. Billings and M. Johnson-Roberson, “Silhonet: An rgb method for 6d object pose estimation,”
2019
Cited alongside, same era.
Y. Hu, J. Hugonot, P. Fua, and M. Salzmann, “Segmentation-driven 6d object pose estimation,” in
2019
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C. Wang, D. Xu, Y. Zhu, R. Martín-Martín, C. Lu, L. Fei-Fei, and S. Savarese, “Densefusion: 6d object pose estimation by iterative dense fusion,” in
2019
Cited alongside, same era.
L. Yang and A. Yao, “Disentangling latent hands for image synthesis and pose estimation,” in
2019
Cited alongside, same era.
S. Baek, K. Kim, and T. Kim, “Pushing the envelope for rgb-based dense 3d hand pose estimation via neural rendering,” in
2019
Cited alongside, same era.
S. Liu, H. Jiang, J. Xu, S. Liu, and X. Wang, “Semi-supervised 3d hand-object poses estimation with interactions in time,” in
2021
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Z. Cao, I. Radosavovic, A. Kanazawa, and J. Malik, “Reconstructing hand-object interactions in the wild,”
2021
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Y. Hasson, G. Varol, C. Schmid, and I. Laptev, “Towards unconstrained joint hand-object reconstruction from rgb videos,” in
2021
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Y. He, H. Huang, H. Fan, Q. Chen, and J. Sun, “Ffb6d: A full flow bidirectional fusion network for 6d pose estimation,” in
2021
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Y. Rong, T. Shiratori, and H. Joo, “Frankmocap: A monocular 3d whole-body pose estimation system via regression and integration,” in
2021
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2019
Cited alongside, same era.
C. Zimmermann, D. Ceylan, J. Yang, B. Russel, M. Argus, and T. Brox, “Freihand: A dataset for markerless capture of hand pose and shape from single rgb images,” in
2019
Cited alongside, same era.
S. Liu, T. Li, W. Chen, and H. Li, “Soft rasterizer: A differentiable renderer for image-based 3d reasoning,”
2019
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M. Nimier-David, D. Vicini, T. Zeltner, and W. Jakob, “Mitsuba 2: A retargetable forward and inverse renderer,”
2019
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O. M. Andrychowicz, B. Baker, M. Chociej, R. Jozefowicz, B. McGrew, J. Pachocki, A. Petron, M. Plappert, G. Powell, A. Ray,
2020
Cited alongside, same era.
T. Brown, B. Mann, N. Ryder, M. Subbiah, J. D. Kaplan, P. Dhariwal, A. Neelakantan, P. Shyam, G. Sastry, A. Askell,
2020
Cited alongside, same era.
S. Hampali, M. Rad, M. Oberweger, and V. Lepetit, “Honnotate: A method for 3d annotation of hand and object poses,” in
2020
Cited alongside, same era.
Y.-W. Chao, W. Yang, Y. Xiang, P. Molchanov, A. Handa, J. Tremblay, Y. S. Narang, K. Van Wyk, U. Iqbal, S. Birchfield, J. Kautz, and D. Fox, “DexYCB: A benchmark for capturing hand grasping of objects,” in
2021
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P. Grady, C. Tang, C. D. Twigg, M. Vo, S. Brahmbhatt, and C. C. Kemp, “Contactopt: Optimizing contact to improve grasps,” in
2021
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2021
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S. K. Dwivedi, N. Athanasiou, M. Kocabas, and M. J. Black, “Learning to regress bodies from images using differentiable semantic rendering,” in
2021
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K. He, X. Chen, S. Xie, Y. Li, P. Dollár, and R. Girshick, “Masked autoencoders are scalable vision learners,” in
2022
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S. Hampali, S. D. Sarkar, M. Rad, and V. Lepetit, “Keypoint transformer: Solving joint identification in challenging hands and object interactions for accurate 3d pose estimation,” in
2022
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Y. Liu, Y. Liu, C. Jiang, K. Lyu, W. Wan, H. Shen, B. Liang, Z. Fu, H. Wang, and L. Yi, “Hoi4d: A 4d egocentric dataset for category-level human-object interaction,” in
2022
Later among the works it cites.
L. Yang, K. Li, X. Zhan, J. Lv, W. Xu, J. Li, and C. Lu, “ArtiBoost: Boosting articulated 3d hand-object pose estimation via online exploration and synthesis,” in
2022
Later among the works it cites.
J. Park, Y. Oh, G. Moon, H. Choi, and K. M. Lee, “Handoccnet: Occlusion-robust 3d hand mesh estimation network,” in
2022
Later among the works it cites.
H. Hu, X. Yi, H. Zhang, J.-H. Yong, and F. Xu, “Physical interaction: Reconstructing hand-object interactions with physics,” in
2022
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E. Heiden, C. E. Denniston, D. Millard, F. Ramos, and G. S. Sukhatme, “Probabilistic inference of simulation parameters via parallel differentiable simulation,”
2022
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S. Christen, M. Kocabas, E. Aksan, J. Hwangbo, J. Song, and O. Hilliges, “D-grasp: Physically plausible dynamic grasp synthesis for hand-object interactions,” in
2022
Later among the works it cites.
D. Turpin, L. Wang, E. Heiden, Y.-C. Chen, M. Macklin, S. Tsogkas, S. Dickinson, and A. Garg, “Grasp’d: Differentiable contact-rich grasp synthesis for multi-fingered hands,” in
2022
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E. Gärtner, M. Andriluka, E. Coumans, and C. Sminchisescu, “Differentiable dynamics for articulated 3d human motion reconstruction,” in
2022
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M. Macklin, “Warp: A high-performance python framework for gpu simulation and graphics,”
2022
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D. Turpin, T. Zhong, S. Zhang, G. Zhu, E. Heiden, M. Macklin, S. Tsogkas, S. Dickinson, and A. Garg, “Fast-grasp’d: Dexterous multi-finger grasp generation through differentiable simulation,” in
2023
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