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Neural reconstruction approaches are rapidly emerging as the preferred representation for 3D scenes, but their limited editability is still posing a challenge.
Generative adversarial nets
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio. 2014 · 2014
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Classifier-free diffusion guidance
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Learning Object-Compositional Neural Radiance Field for Editable Scene Rendering. In
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Large scale image completion via co-modulated generative adversarial networks
Shengyu Zhao, Jonathan Cui, Yilun Sheng, Yue Dong, Xiao Liang, Eric I Chang, and Yan Xu. 2021 · 2021
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Blended diffusion for text-driven editing of natural images. In
Omri Avrahami, Dani Lischinski, and Ohad Fried. 2022 · 2022
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eDiff-I: Text-to-Image Diffusion Models with Ensemble of Expert Denoisers
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Mip-NeRF 360: Unbounded Anti-Aliased Neural Radiance Fields
Jonathan T. Barron, Ben Mildenhall, Dor Verbin, Pratul P. Srinivasan, and Peter Hedman. 2022 · 2022
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GAUDI: A Neural Architect for Immersive 3D Scene Generation. In
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An image is worth one word: Personalizing text-to-image generation using textual inversion
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LoRA: Low-rank adaptation of large language models
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Tetrahedral Diffusion Models for 3D Shape Generation
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Sdedit: Image synthesis and editing with stochastic differential equations
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 · 2023
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Reference-guided Controllable Inpainting of Neural Radiance Fields
Ashkan Mirzaei, Tristan Aumentado-Armstrong, Marcus A Brubaker, Jonathan Kelly, Alex Levinshtein, Konstantinos G Derpanis, and Igor Gilitschenski. 2023a · 2023
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DiffusionLight: Light Probes for Free by Painting a Chrome Ball
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Ben Poole, Ajay Jain, Jonathan T. Barron, and Ben Mildenhall. 2023 · 2023
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Chenlin Meng, Yang Song, Jiaming Song, Jiajun Wu, Jun-Yan Zhu, and Stefano Ermon. 2022 · 2022
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Point-E: A System for Generating 3D Point Clouds from Complex Prompts
Alex Nichol, Heewoo Jun, Prafulla Dhariwal, Pamela Mishkin, and Mark Chen. 2022 · 2022
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Resolution-robust large mask inpainting with fourier convolutions. In
Roman Suvorov, Elizaveta Logacheva, Anton Mashikhin, Anastasia Remizova, Arsenii Ashukha, Aleksei Silvestrov, Naejin Kong, Harshith Goka, Kiwoong Park, and Victor Lempitsky. 2022 · 2022
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LION: Latent Point Diffusion Models for 3D Shape Generation. In
Xiaohui Zeng, Arash Vahdat, Francis Williams, Zan Gojcic, Or Litany, Sanja Fidler, and Karsten Kreis. 2022 · 2022
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Image inpainting with cascaded modulation GAN and object-aware training. In
Haitian Zheng, Zhe Lin, Jingwan Lu, Scott Cohen, Eli Shechtman, Connelly Barnes, Jianming Zhang, Ning Xu, Sohrab Amirghodsi, and Jiebo Luo. 2022 · 2022
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Personalized Restoration via Dual-Pivot Tuning
Pradyumna Chari, Sizhuo Ma, Daniil Ostashev, Achuta Kadambi, Gurunandan Krishnan, Jian Wang, and Kfir Aberman. 2023 · 2023
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Fantasia3D: Disentangling Geometry and Appearance for High-quality Text-to-3D Content Creation. In
Rui Chen, Yongwei Chen, Ningxin Jiao, and Kui Jia. 2023 · 2023
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Inpaint3D: 3D Scene Content Generation using 2D Inpainting Diffusion
Kira Prabhu, Jane Wu, Lynn Tsai, Peter Hedman, Dan B Goldman, Ben Poole, and Michael Broxton. 2023 · 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 · 2023
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GANeRF: Leveraging Discriminators to Optimize Neural Radiance Fields
Barbara Roessle, Norman Müller, Lorenzo Porzi, Samuel Rota Bulò, Peter Kontschieder, and Matthias Nießner. 2023 · 2023
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DreamBooth: Fine Tuning Text-to-image Diffusion Models for Subject-Driven Generation
Nataniel Ruiz, Yuanzhen Li, Varun Jampani, Yael Pritch, Michael Rubinstein, and Kfir Aberman. 2023 · 2023
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ZipLoRA: Any Subject in Any Style by Effectively Merging LoRAs
Viraj Shah, Nataniel Ruiz, Forrester Cole, Erika Lu, Svetlana Lazebnik, Yuanzhen Li, and Varun Jampani. 2023 · 2023
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Dreamcraft3d: Hierarchical 3d generation with bootstrapped diffusion prior
Jingxiang Sun, Bo Zhang, Ruizhi Shao, Lizhen Wang, Wen Liu, Zhenda Xie, and Yebin Liu. 2023 · 2023
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RealFill: Reference-Driven Generation for Authentic Image Completion
Luming Tang, Nataniel Ruiz, Chu Qinghao, Yuanzhen Li, Aleksander Holynski, David E Jacobs, Bharath Hariharan, Yael Pritch, Neal Wadhwa, Kfir Aberman, and Michael Rubinstein. 2023 · 2023
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InpaintNeRF360: Text-Guided 3D Inpainting on Unbounded Neural Radiance Fields
Dongqing Wang, Tong Zhang, Alaa Abboud, and Sabine Süsstrunk. 2023b · 2023
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NeRFiller: Completing Scenes via Generative 3D Inpainting
Ethan Weber, Aleksander Hołyński, Varun Jampani, Saurabh Saxena, Noah Snavely, Abhishek Kar, and Angjoo Kanazawa. 2023 · 2023
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Removing objects from neural radiance fields. In
Silvan Weder, Guillermo Garcia-Hernando, Aron Monszpart, Marc Pollefeys, Gabriel J Brostow, Michael Firman, and Sara Vicente. 2023 · 2023
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ReconFusion: 3D Reconstruction with Diffusion Priors
Rundi Wu, Ben Mildenhall, Philipp Henzler, Keunhong Park, Ruiqi Gao, Daniel Watson, Pratul P. Srinivasan, Dor Verbin, Jonathan T. Barron, Ben Poole, and Aleksander Holynski. 2023 · 2023
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Smartbrush: Text and shape guided object inpainting with diffusion model. In
Shaoan Xie, Zhifei Zhang, Zhe Lin, Tobias Hinz, and Kun Zhang. 2023 · 2023
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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 · 2023
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