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Current 4D generation methods have achieved noteworthy efficacy with the aid of advanced diffusion generative models.
Auto-encoding variational bayes
Diederik P Kingma and Max Welling · 2014
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The unreasonable effectiveness of deep features as a perceptual metric
Richard Zhang, Phillip Isola, Alexei A Efros, Eli Shechtman, and Oliver Wang · 2018
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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 · 2020
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Emerging properties in self-supervised vision transformers
Mathilde Caron, Hugo Touvron, Ishan Misra, Hervé Jégou, Julien Mairal, Piotr Bojanowski, and Armand Joulin · 2021
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Learning transferable visual models from natural language supervision
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, Gretchen Krueger, and Sutskever Ilya · 2021
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Denoising diffusion implicit models
Jiaming Song, Chenlin Meng, and Stefano Ermon · 2021
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Efficient geometry-aware 3d generative adversarial networks
Eric R Chan, Connor Z Lin, Matthew A Chan, Koki Nagano, Boxiao Pan, Shalini De Mello, Orazio Gallo, Leonidas J Guibas, Jonathan Tremblay, Sameh Khamis, Tero Karras, and Gordon Wetzstein · 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, and Zhaoyang Lv · 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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High-resolution image synthesis with latent diffusion models
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer · 2022
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Renderdiffusion: Image diffusion for 3d reconstruction, inpainting and generation
Titas Anciukevičius, Zexiang Xu, Matthew Fisher, Paul Henderson, Hakan Bilen, Niloy J Mitra, and Paul Guerrero · 2023
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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, Varun Jampani, and Rodin Rombach · 2023
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Hexplane: A fast representation for dynamic scenes
Ang Cao and Justin Johnson · 2023
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Fantasia3d: Disentangling geometry and appearance for high-quality text-to-3d content creation
Rui Chen, Yongwei Chen, Ningxin Jiao, and Kui Jia · 2023
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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
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Hyperdiffusion: Generating implicit neural fields with weight-space diffusion
Ziya Erkoç, Fangchang Ma, Qi Shan, Matthias Nießner, and Angela Dai · 2023
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K-planes: Explicit radiance fields in space, time, and appearance
Sara Fridovich-Keil, Giacomo Meanti, Frederik Rahbæk Warburg, Benjamin Recht, and Angjoo Kanazawa · 2023
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I2v-adapter: A general image-to-video adapter for video diffusion models
Xun Guo, Mingwu Zheng, Liang Hou, Yuan Gao, Yufan Deng, Pengfei Wan, Di Zhang, Yufan Liu, Weiming Hu, Zhengjun Zha, Haibin Huang, and Chongyang Ma · 2023
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threestudio: A unified framework for 3d content generation
Yuan-Chen Guo, Ying-Tian Liu, Ruizhi Shao, Christian Laforte, Vikram Voleti, Guan Luo, Chia-Hao Chen, Zi-Xin Zou, Chen Wang, Yan-Pei Cao, and Song-Hai Zhang · 2023
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3dgen: Triplane latent diffusion for textured mesh generation
Anchit Gupta, Wenhan Xiong, Yixin Nie, Ian Jones, and Barlas Oğuz · 2023
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3d gaussian splatting for real-time radiance field rendering
Bernhard Kerbl, Georgios Kopanas, Thomas Leimkühler, and George Drettakis · 2023
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Nerfacc: Efficient sampling accelerates nerfs
Ruilong Li, Hang Gao, Matthew Tancik, and Angjoo Kanazawa · 2023
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Magic3d: High-resolution text-to-3d content creation
Chen-Hsuan Lin, Jun Gao, Luming Tang, Towaki Takikawa, Xiaohui Zeng, Xun Huang, Karsten Kreis, Sanja Fidler, Ming-Yu Liu, and Tsung-Yi Lin · 2023
Cited alongside, same era.
Consistent123: One image to highly consistent 3d asset using case-aware diffusion priors
Yukang Lin, Haonan Han, Chaoqun Gong, Zunnan Xu, Yachao Zhang, and Xiu Li · 2023
Cited alongside, same era.
Zero-1-to-3: Zero-shot one image to 3d object
Ruoshi Liu, Rundi Wu, Basile Van Hoorick, Pavel Tokmakov, Sergey Zakharov, and Carl Vondrick · 2023
Cited alongside, same era.
Scalable 3d captioning with pretrained models
Tiange Luo, Chris Rockwell, Honglak Lee, and Justin Johnson · 2023
Cited alongside, same era.
Realfusion: 360° reconstruction of any object from a single image
Luke Melas-Kyriazi, Iro Laina, Christian Rupprecht, and Andrea Vedaldi · 2023
Cited alongside, same era.
V3d: Video diffusion models are effective 3d generators
Zilong Chen, Yikai Wang, Feng Wang, Zhengyi Wang, and Huaping Liu · 2024
Closest in time.
Animatediff: Animate your personalized text-to-image diffusion models without specific tuning
Yuwei Guo, Ceyuan Yang, Anyi Rao, Yaohui Wang, Yu Qiao, Dahua Lin, and Bo Dai · 2024
Closest in time.
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 · 2024
Closest in time.
Sc-gs: Sparse-controlled gaussian splatting for editable dynamic scenes
Yi-Hua Huang, Yang-Tian Sun, Ziyi Yang, Xiaoyang Lyu, Yan-Pei Cao, and Xiaojuan Qi · 2024
Closest in time.
Consistent4d: Consistent 360° dynamic object generation from monocular video
Yanqin Jiang, Li Zhang, Jin Gao, Weimin Hu, and Yao Yao · 2024
Closest in time.
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Norman Müller, Yawar Siddiqui, Lorenzo Porzi, Samuel Rota Bulo, Peter Kontschieder, and Matthias Nießner · 2023
Cited alongside, same era.
Dreamfusion: Text-to-3d using 2d diffusion
Ben Poole, Ajay Jain, Jonathan T Barron, and Ben Mildenhall · 2023
Cited alongside, same era.
Dreambooth3d: Subject-driven text-to-3d generation
Amit Raj, Srinivas Kaza, Ben Poole, Michael Niemeyer, Nataniel Ruiz, Ben Mildenhall, Shiran Zada, Kfir Aberman, Michael Rubinstein, Jonathan Barron, Yuanzhen Li, and Varun Jampani · 2023
Cited alongside, same era.
Dreamgaussian4d: Generative 4d gaussian splatting
Jiawei Ren, Liang Pan, Jiaxiang Tang, Chi Zhang, Ang Cao, Gang Zeng, and Ziwei Liu · 2023
Cited alongside, same era.
3d neural field generation using triplane diffusion
J Ryan Shue, Eric Ryan Chan, Ryan Po, Zachary Ankner, Jiajun Wu, and Gordon Wetzstein · 2023
Cited alongside, same era.
Make-a-video: Text-to-video generation without text-video data
Uriel Singer, Adam Polyak, Thomas Hayes, Xi Yin, Jie An, Songyang Zhang, Qiyuan Hu, Harry Yang, Oron Ashual, Oran Gafni, Devi Parikh, Sonal Gupta, and Yaniv Taigman · 2023
Cited alongside, same era.
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, and Yaniv Taigman · 2023
Cited alongside, same era.
Instant3d: Fast text-to-3d with sparse-view generation and large reconstruction model
Jiahao Li, Hao Tan, Kai Zhang, Zexiang Xu, Fujun Luan, Yinghao Xu, Yicong Hong, Kalyan Sunkavalli, Greg Shakhnarovich, and Sai Bi · 2024
Closest in time.
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 · 2024
Closest in time.
Humangaussian: Text-driven 3d human generation with gaussian splatting
Xian Liu, Xiaohang Zhan, Jiaxiang Tang, Ying Shan, Gang Zeng, Dahua Lin, Xihui Liu, and Ziwei Liu · 2024
Closest in time.
Syncdreamer: Generating multiview-consistent images from a single-view image
Yuan Liu, Cheng Lin, Zijiao Zeng, Xiaoxiao Long, Lingjie Liu, Taku Komura, and Wenping Wang · 2024
Closest in time.
Wonder3d: Single image to 3d using cross-domain diffusion
Xiaoxiao Long, Yuan-Chen Guo, Cheng Lin, Yuan Liu, Zhiyang Dou, Lingjie Liu, Yuexin Ma, Song-Hai Zhang, Marc Habermann, Christian Theobalt, and wenping Wang · 2024
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, and Bernard Ghanem · 2024
Closest in time.
Mvdream: Multi-view diffusion for 3d generation
Yichun Shi, Peng Wang, Jianglong Ye, Mai Long, Kejie Li, and Xiao Yang · 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.
Dreamgaussian: Generative gaussian splatting for efficient 3d content creation
Jiaxiang Tang, Jiawei Ren, Hang Zhou, Ziwei Liu, and Gang Zeng · 2024
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 · 2024
Closest in time.
Sc4d: Sparse-controlled video-to-4d generation and motion transfer
Zijie Wu, Chaohui Yu, Yanqin Jiang, Chenjie Cao, Fan Wang, and Xiang Bai · 2024
Closest in time.
Dmv3d: Denoising multi-view diffusion using 3d large reconstruction model
Yinghao Xu, Hao Tan, Fujun Luan, Sai Bi, Peng Wang, Jiahao Li, Zifan Shi, Kalyan Sunkavalli, Gordon Wetzstein, Zexiang Xu, et al · 2024
Closest in time.
Consistnet: Enforcing 3d consistency for multi-view images diffusion
Jiayu Yang, Ziang Cheng, Yunfei Duan, Pan Ji, and Hongdong Li · 2024
Closest in time.
Mosaic-sdf for 3d generative models
Lior Yariv, Omri Puny, Natalia Neverova, Oran Gafni, and Yaron Lipman · 2024
Closest in time.
Stag4d: Spatial-temporal anchored generative 4d gaussians
Yifei Zeng, Yanqin Jiang, Siyu Zhu, Yuanxun Lu, Youtian Lin, Hao Zhu, Weiming Hu, Xun Cao, and Yao Yao · 2024
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 · 2024
Closest in time.