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4D content generation has achieved remarkable progress recently.
Shapenet: An information-rich 3d model repository
Angel X Chang, Thomas Funkhouser, Leonidas Guibas, Pat Hanrahan, Qixing Huang, Zimo Li, Silvio Savarese, Manolis Savva, Shuran Song, Hao Su, et al · 2015
Earlier work this paper cites.
Learning implicit fields for generative shape modeling
Zhiqin Chen and Hao Zhang · 2019
Earlier work this paper cites.
Disn: Deep implicit surface network for high-quality single-view 3d reconstruction
Qiangeng Xu, Weiyue Wang, Duygu Ceylan, Radomir Mech, and Ulrich Neumann · 2019
Earlier work this paper cites.
Bsp-net: Generating compact meshes via binary space partitioning
Zhiqin Chen, Andrea Tagliasacchi, and Hao Zhang · 2020
Earlier work this paper cites.
Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
Earlier work this paper cites.
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 · 2020
Earlier work this paper cites.
Neural radiance flow for 4d view synthesis and video processing
Yilun Du, Yinan Zhang, Hong-Xing Yu, Joshua B Tenenbaum, and Jiajun Wu · 2021
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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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Neural scene flow fields for space-time view synthesis of dynamic scenes
Zhengqi Li, Simon Niklaus, Noah Snavely, and Oliver Wang · 2021
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Nerfies: Deformable neural radiance fields
Keunhong Park, Utkarsh Sinha, Jonathan T Barron, Sofien Bouaziz, Dan B Goldman, Steven M Seitz, and Ricardo Martin-Brualla · 2021
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Hypernerf: A higher-dimensional representation for topologically varying neural radiance fields
Keunhong Park, Utkarsh Sinha, Peter Hedman, Jonathan T Barron, Sofien Bouaziz, Dan B Goldman, Ricardo Martin-Brualla, and Steven M Seitz · 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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Non-rigid neural radiance fields: Reconstruction and novel view synthesis of a dynamic scene from monocular video
Edgar Tretschk, Ayush Tewari, Vladislav Golyanik, Michael Zollhöfer, Christoph Lassner, and Christian Theobalt · 2021
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Grf: Learning a general radiance field for 3d representation and rendering
Alex Trevithick and Bo Yang · 2021
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Space-time neural irradiance fields for free-viewpoint video
Wenqi Xian, Jia-Bin Huang, Johannes Kopf, and Changil Kim · 2021
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Star: Self-supervised tracking and reconstruction of rigid objects in motion with neural rendering
Wentao Yuan, Zhaoyang Lv, Tanner Schmidt, and Steven Lovegrove · 2021
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Topologically-aware deformation fields for single-view 3d reconstruction
Shivam Duggal and Deepak Pathak · 2022
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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
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Neurofluid: Fluid dynamics grounding with particle-driven neural radiance fields
Shanyan Guan, Huayu Deng, Yunbo Wang, and Xiaokang Yang · 2022
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Neural 3d video synthesis from multi-view video
Tianye Li, Mira Slavcheva, Michael Zollhoefer, Simon Green, Christoph Lassner, Changil Kim, Tanner Schmidt, Steven Lovegrove, Michael Goesele, Richard Newcombe, et al · 2022
Earlier work this paper cites.
Point-e: A system for generating 3d point clouds from complex prompts
Alex Nichol, Heewoo Jun, Prafulla Dhariwal, Pamela Mishkin, and Mark Chen · 2022
Cited alongside, same era.
Dreamfusion: Text-to-3d using 2d diffusion
Ben Poole, Ajay Jain, Jonathan T Barron, and Ben Mildenhall · 2022
Cited alongside, same era.
High-resolution image synthesis with latent diffusion models
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer · 2022
Cited alongside, same era.
Knn-diffusion: Image generation via large-scale retrieval
Shelly Sheynin, Oron Ashual, Adam Polyak, Uriel Singer, Oran Gafni, Eliya Nachmani, and Yaniv Taigman · 2022
Cited alongside, same era.
4d-fy: Text-to-4d generation using hybrid score distillation sampling
Dynamic 3d gaussians: Tracking by persistent dynamic view synthesis
Jonathon Luiten, Georgios Kopanas, Bastian Leibe, and Deva Ramanan · 2023
Closest in time.
Realfusion: 360deg reconstruction of any object from a single image
Luke Melas-Kyriazi, Iro Laina, Christian Rupprecht, and Andrea Vedaldi · 2023
Closest in time.
Magic123: One image to high-quality 3d object generation using both 2d and 3d diffusion priors
Guocheng Qian, Jinjie Mai, Abdullah Hamdi, Jian Ren, Aliaksandr Siarohin, Bing Li, Hsin-Ying Lee, Ivan Skorokhodov, Peter Wonka, Sergey Tulyakov, et al · 2023
Closest in time.
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
Closest in time.
Zero123++: a single image to consistent multi-view diffusion base model, 2023
Ruoxi Shi, Hansheng Chen, Zhuoyang Zhang, Minghua Liu, Chao Xu, Xinyue Wei, Linghao Chen, Chong Zeng, and Hao Su · 2023
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Sherwin Bahmani, Ivan Skorokhodov, Victor Rong, Gordon Wetzstein, Leonidas Guibas, Peter Wonka, Sergey Tulyakov, Jeong Joon Park, Andrea Tagliasacchi, and David B Lindell · 2023
Cited alongside, same era.
Stable video diffusion: Scaling latent video diffusion models to large datasets
Andreas Blattmann, Tim Dockhorn, Sumith Kulal, Daniel Mendelevitch, Maciej Kilian, Dominik Lorenz, Yam Levi, Zion English, Vikram Voleti, Adam Letts, et al · 2023
Cited alongside, same era.
Hexplane: A fast representation for dynamic scenes
Ang Cao and Justin Johnson · 2023
Cited alongside, same era.
Fantasia3d: Disentangling geometry and appearance for high-quality text-to-3d content creation
Rui Chen, Yongwei Chen, Ningxin Jiao, and Kui Jia · 2023
Cited alongside, same era.
Objaverse-xl: A universe of 10m+ 3d objects
Matt Deitke, Ruoshi Liu, Matthew Wallingford, Huong Ngo, Oscar Michel, Aditya Kusupati, Alan Fan, Christian Laforte, Vikram Voleti, Samir Yitzhak Gadre, et al · 2023
Cited alongside, same era.
Objaverse: A universe of annotated 3d objects
Matt Deitke, Dustin Schwenk, Jordi Salvador, Luca Weihs, Oscar Michel, Eli VanderBilt, Ludwig Schmidt, Kiana Ehsani, Aniruddha Kembhavi, and Ali Farhadi · 2023
Cited alongside, same era.
K-planes: Explicit radiance fields in space, time, and appearance
Sara Fridovich-Keil, Giacomo Meanti, Frederik Rahbæk Warburg, Benjamin Recht, and Angjoo Kanazawa · 2023
Cited alongside, same era.
Lrm: Large reconstruction model for single image to 3d
Yicong Hong, Kai Zhang, Jiuxiang Gu, Sai Bi, Yang Zhou, Difan Liu, Feng Liu, Kalyan Sunkavalli, Trung Bui, and Hao Tan · 2023
Cited alongside, same era.
Closest in time.
Text-to-4d dynamic scene generation
Uriel Singer, Shelly Sheynin, Adam Polyak, Oron Ashual, Iurii Makarov, Filippos Kokkinos, Naman Goyal, Andrea Vedaldi, Devi Parikh, Justin Johnson, et al · 2023
Closest in time.
Splatter image: Ultra-fast single-view 3d reconstruction
Stanislaw Szymanowicz, Christian Rupprecht, and Andrea Vedaldi · 2023
Closest in time.
Dreamgaussian: Generative gaussian splatting for efficient 3d content creation
Jiaxiang Tang, Jiawei Ren, Hang Zhou, Ziwei Liu, and Gang Zeng · 2023
Closest in time.
Make-it-3d: High-fidelity 3d creation from a single image with diffusion prior
Junshu Tang, Tengfei Wang, Bo Zhang, Ting Zhang, Ran Yi, Lizhuang Ma, and Dong Chen · 2023
Closest in time.
Suds: Scalable urban dynamic scenes
Haithem Turki, Jason Y Zhang, Francesco Ferroni, and Deva Ramanan · 2023
Closest in time.
Lavie: High-quality video generation with cascaded latent diffusion models
Yaohui Wang, Xinyuan Chen, Xin Ma, Shangchen Zhou, Ziqi Huang, Yi Wang, Ceyuan Yang, Yinan He, Jiashuo Yu, Peiqing Yang, et al · 2023
Closest in time.
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
Closest in time.
Deformable 3d gaussians for high-fidelity monocular dynamic scene reconstruction
Ziyi Yang, Xinyu Gao, Wen Zhou, Shaohui Jiao, Yuqing Zhang, and Xiaogang Jin · 2023
Closest in time.
Mvimgnet: A large-scale dataset of multi-view images
Xianggang Yu, Mutian Xu, Yidan Zhang, Haolin Liu, Chongjie Ye, Yushuang Wu, Zizheng Yan, Tianyou Liang, Guanying Chen, Shuguang Cui, and Xiaoguang Han · 2023
Closest in time.
Animate124: Animating one image to 4d dynamic scene
Yuyang Zhao, Zhiwen Yan, Enze Xie, Lanqing Hong, Zhenguo Li, and Gim Hee Lee · 2023
Closest in time.
A unified approach for text-and image-guided 4d scene generation
Yufeng Zheng, Xueting Li, Koki Nagano, Sifei Liu, Otmar Hilliges, and Shalini De Mello · 2023
Closest in time.
Particlenerf: A particle-based encoding for online neural radiance fields
Jad Abou-Chakra, Feras Dayoub, and Niko Sünderhauf · 2024
Closest in time.
Gaussianflow: Splatting gaussian dynamics for 4d content creation
Quankai Gao, Qiangeng Xu, Zhe Cao, Ben Mildenhall, Wenchao Ma, Le Chen, Danhang Tang, and Ulrich Neumann · 2024
Closest in time.
Creating video from text, 2024
Sora Team OpenAI · 2024
Closest in time.
Lgm: Large multi-view gaussian model for high-resolution 3d content creation
Jiaxiang Tang, Zhaoxi Chen, Xiaokang Chen, Tengfei Wang, Gang Zeng, and Ziwei Liu · 2024
Closest in time.