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In recent years, there has been rapid development in 3D generation models, opening up new possibilities for applications such as simulating the dynamic movements of 3D objects and customizing their behaviors.
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Jan Rychlewski · 1984
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Elastically deformable models
Demetri Terzopoulos, John Platt, Alan Barr, and Kurt Fleischer · 1987
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Modeling inelastic deformation: viscolelasticity, plasticity, fracture
Demetri Terzopoulos and Kurt Fleischer · 1988
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Richard M Christensen · 2003
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Aapo Hyvärinen and Peter Dayan · 2005
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Particle-spring systems for structural form finding
Axel Kilian and John Ochsendorf · 2005
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Auto-encoding variational bayes
Diederik P Kingma and Max Welling · 2013
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A material point method for snow simulation
Alexey Stomakhin, Craig Schroeder, Lawrence Chai, Joseph Teran, and Andrew Selle · 2013
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The affine particle-in-cell method
Chenfanfu Jiang, Craig Schroeder, Andrew Selle, Joseph Teran, and Alexey Stomakhin · 2015
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Dynamicfusion: Reconstruction and tracking of non-rigid scenes in real-time
Richard A Newcombe, Dieter Fox, and Steven M Seitz · 2015
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A material point method for viscoelastic fluids, foams and sponges
Daniel Ram, Theodore Gast, Chenfanfu Jiang, Craig Schroeder, Alexey Stomakhin, Joseph Teran, and Pirouz Kavehpour · 2015
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Continuum foam: A material point method for shear-dependent flows
Yonghao Yue, Breannan Smith, Christopher Batty, Changxi Zheng, and Eitan Grinspun · 2015
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The material point method for simulating continuum materials
Chenfanfu Jiang, Craig Schroeder, Joseph Teran, Alexey Stomakhin, and Andrew Selle · 2016
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Drucker-prager elastoplasticity for sand animation
Gergely Klár, Theodore Gast, Andre Pradhana, Chuyuan Fu, Craig Schroeder, Chenfanfu Jiang, and Joseph Teran · 2016
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A moving least squares material point method with displacement discontinuity and two-way rigid body coupling
Yuanming Hu, Yu Fang, Ziheng Ge, Ziyin Qu, Yixin Zhu, Andre Pradhana, and Chenfanfu Jiang · 2018
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A moving least squares material point method with displacement discontinuity and two-way rigid body coupling
Yuanming Hu, Yu Fang, Ziheng Ge, Ziyin Qu, Yixin Zhu, Andre Pradhana, and Chenfanfu Jiang · 2018
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Silly rubber: an implicit material point method for simulating non-equilibrated viscoelastic and elastoplastic solids
Yu Fang, Minchen Li, Ming Gao, and Chenfanfu Jiang · 2019
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Generative adversarial networks
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2020
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Denoising Diffusion Probabilistic Models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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Dynamic view synthesis from dynamic monocular video
Chen Gao, Ayush Saraf, Johannes Kopf, and Jia-Bin Huang · 2021
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Variational diffusion models
Diederik P Kingma, Tim Salimans, Ben Poole, and Jonathan Ho · 2021
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Nerf: Representing scenes as neural radiance fields for view synthesis
Ben Mildenhall, Pratul P Srinivasan, Matthew Tancik, Jonathan T Barron, Ravi Ramamoorthi, and Ren Ng · 2021
3d gaussian splatting for real-time radiance field rendering
Bernhard Kerbl, Georgios Kopanas, Thomas Leimkühler, and George Drettakis · 2023
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Videopoet: A large language model for zero-shot video generation
Dan Kondratyuk, Lijun Yu, Xiuye Gu, José Lezama, Jonathan Huang, Rachel Hornung, Hartwig Adam, Hassan Akbari, Yair Alon, Vighnesh Birodkar, et al · 2023
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Dynmf: Neural motion factorization for real-time dynamic view synthesis with 3d gaussian splatting
Agelos Kratimenos, Jiahui Lei, and Kostas Daniilidis · 2023
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Align your gaussians: Text-to-4d with dynamic 3d gaussians and composed diffusion models
Huan Ling, Seung Wook Kim, Antonio Torralba, Sanja Fidler, and Karsten Kreis · 2023
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Sherpa3D: Boosting high-fidelity text-to-3d generation via coarse 3d prior
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Improved Denoising Diffusion Probabilistic Models
Alexander Quinn Nichol and Prafulla Dhariwal · 2021
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D-nerf: Neural radiance fields for dynamic scenes
Albert Pumarola, Enric Corona, Gerard Pons-Moll, and Francesc Moreno-Noguer · 2021
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Fast dynamic radiance fields with time-aware neural voxels
Jiemin Fang, Taoran Yi, Xinggang Wang, Lingxi Xie, Xiaopeng Zhang, Wenyu Liu, Matthias Nießner, and Qi Tian · 2022
Cited alongside, same era.
Imagen video: High definition video generation with diffusion models
Jonathan Ho, William Chan, Chitwan Saharia, Jay Whang, Ruiqi Gao, Alexey Gritsenko, Diederik P Kingma, Ben Poole, Mohammad Norouzi, David J Fleet, et al · 2022
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Cogvideo: Large-scale pretraining for text-to-video generation via transformers
Wenyi Hong, Ming Ding, Wendi Zheng, Xinghan Liu, and Jie Tang · 2022
Cited alongside, same era.
Pac-nerf: Physics augmented continuum neural radiance fields for geometry-agnostic system identification
Xuan Li, Yi-Ling Qiao, Peter Yichen Chen, Krishna Murthy Jatavallabhula, Ming Lin, Chenfanfu Jiang, and Chuang Gan · 2022
Cited alongside, same era.
Fangfu Liu, Diankun Wu, Yi Wei, Yongming Rao, and Yueqi Duan · 2023
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Dynamic 3d gaussians: Tracking by persistent dynamic view synthesis
Jonathon Luiten, Georgios Kopanas, Bastian Leibe, and Deva Ramanan · 2023
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BlenderNeRF, May 2023
Maxime Raafat · 2023
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Dreamgaussian4d: Generative 4d gaussian splatting
Jiawei Ren, Liang Pan, Jiaxiang Tang, Chi Zhang, Ang Cao, Gang Zeng, and Ziwei Liu · 2023
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Tensor4d: Efficient neural 4d decomposition for high-fidelity dynamic reconstruction and rendering
Ruizhi Shao, Zerong Zheng, Hanzhang Tu, Boning Liu, Hongwen Zhang, and Yebin Liu · 2023
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Dreamgaussian: Generative gaussian splatting for efficient 3d content creation
Jiaxiang Tang, Jiawei Ren, Hang Zhou, Ziwei Liu, and Gang Zeng · 2023
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Suds: Scalable urban dynamic scenes
Haithem Turki, Jason Y Zhang, Francesco Ferroni, and Deva Ramanan · 2023
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Modelscope text-to-video technical report
Jiuniu Wang, Hangjie Yuan, Dayou Chen, Yingya Zhang, Xiang Wang, and Shiwei Zhang · 2023
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4d gaussian splatting for real-time dynamic scene rendering
Guanjun Wu, Taoran Yi, Jiemin Fang, Lingxi Xie, Xiaopeng Zhang, Wei Wei, Wenyu Liu, Qi Tian, and Xinggang Wang · 2023
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Physgaussian: Physics-integrated 3d gaussians for generative dynamics
Tianyi Xie, Zeshun Zong, Yuxin Qiu, Xuan Li, Yutao Feng, Yin Yang, and Chenfanfu Jiang · 2023
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Deformable 3d gaussians for high-fidelity monocular dynamic scene reconstruction
Ziyi Yang, Xinyu Gao, Wen Zhou, Shaohui Jiao, Yuqing Zhang, and Xiaogang Jin · 2023
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Neural stress fields for reduced-order elastoplasticity and fracture
Zeshun Zong, Xuan Li, Minchen Li, Maurizio M Chiaramonte, Wojciech Matusik, Eitan Grinspun, Kevin Carlberg, Chenfanfu Jiang, and Peter Yichen Chen · 2023
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Particlenerf: A particle-based encoding for online neural radiance fields
Jad Abou-Chakra, Feras Dayoub, and Niko Sünderhauf · 2024
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Lumiere: A space-time diffusion model for video generation
Omer Bar-Tal, Hila Chefer, Omer Tov, Charles Herrmann, Roni Paiss, Shiran Zada, Ariel Ephrat, Junhwa Hur, Yuanzhen Li, Tomer Michaeli, et al · 2024
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Video generation models as world simulators
Tim Brooks, Bill Peebles, Connor Homes, Will DePue, Yufei Guo, Li Jing, David Schnurr, Joe Taylor, Troy Luhman, Eric Luhman, Clarence Ng, Ricky Wang, and Aditya Ramesh · 2024
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Advances in 3d generation: A survey
Xiaoyu Li, Qi Zhang, Di Kang, Weihao Cheng, Yiming Gao, Jingbo Zhang, Zhihao Liang, Jing Liao, Yan-Pei Cao, and Ying Shan · 2024
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Make-Your-3D: Fast and consistent subject-driven 3d content generation
Fangfu Liu, Hanyang Wang, Weiliang Chen, Haowen Sun, and Yueqi Duan · 2024
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Crm: Single image to 3d textured mesh with convolutional reconstruction model
Zhengyi Wang, Yikai Wang, Yifei Chen, Chendong Xiang, Shuo Chen, Dajiang Yu, Chongxuan Li, Hang Su, and Jun Zhu · 2024
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Physdreamer: Physics-based interaction with 3d objects via video generation
Tianyuan Zhang, Hong-Xing Yu, Rundi Wu, Brandon Y Feng, Changxi Zheng, Noah Snavely, Jiajun Wu, and William T Freeman · 2024
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