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We present a novel 3D shape completion framework that unifies multimodal conditioning, leveraging both 2D images and 3D partial scans through a latent diffusion model.
A volumetric method for building complex models from range images
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Temporally coherent completion of dynamic shapes
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Shapenet: An information-rich 3d model repository
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Improved adam optimizer for deep neural networks
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Scan2mesh: From unstructured range scans to 3d meshes
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Deepsdf: Learning continuous signed distance functions for shape representation
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View-based 3-d cad model retrieval with deep residual networks
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Sg-nn: Sparse generative neural networks for self-supervised scene completion of rgb-d scans
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A conditional point diffusion-refinement paradigm for 3d point cloud completion
Zhaoyang Lyu, Zhifeng Kong, Xudong Xu, Liang Pan, and Dahua Lin · 2021
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Learning transferable visual models from natural language supervision
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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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Progressive distillation for fast sampling of diffusion models
Tim Salimans and Jonathan Ho · 2022
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Learning to complete object shapes for object-level mapping in dynamic scenes
Binbin Xu, Andrew J Davison, and Stefan Leutenegger · 2022
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Shapeformer: Transformer-based shape completion via sparse representation
Xingguang Yan, Liqiang Lin, Niloy J Mitra, Dani Lischinski, Daniel Cohen-Or, and Hui Huang · 2022
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Sdfusion: Multimodal 3d shape completion, reconstruction, and generation
Yen-Chi Cheng, Hsin-Ying Lee, Sergey Tulyakov, Alexander G Schwing, and Liang-Yan Gui · 2023
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High-resolution image synthesis with latent diffusion models, 2021
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer · 2021
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Unsupervised 3d shape completion through gan inversion
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3d shape generation and completion through point-voxel diffusion
Linqi Zhou, Yilun Du, and Jiajun Wu · 2021
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Neural rgb-d surface reconstruction
Dejan Azinović, Ricardo Martin-Brualla, Dan B Goldman, Matthias Nießner, and Justus Thies · 2022
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Weakly-supervised end-to-end cad retrieval to scan objects
Tim Beyer and Angela Dai · 2022
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Latent-nerf for shape-guided generation of 3d shapes and textures
Gal Metzer, Elad Richardson, Or Patashnik, Raja Giryes, and Daniel Cohen-Or · 2022
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Autosdf: Shape priors for 3d completion, reconstruction and generation
Paritosh Mittal, Yen-Chi Cheng, Maneesh Singh, and Shubham Tulsiani · 2022
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Diffusion-sdf: Conditional generative modeling of signed distance functions
Gene Chou, Yuval Bahat, and Felix Heide · 2023
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Diffcomplete: Diffusion-based generative 3d shape completion
Ruihang Chu, Enze Xie, Shentong Mo, Zhenguo Li, Matthias Nießner, Chi-Wing Fu, and Jiaya Jia · 2023
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Point-cloud completion with pretrained text-to-image diffusion models
Yoni Kasten, Ohad Rahamim, and Gal Chechik · 2023
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Generalized deep 3d shape prior via part-discretized diffusion process
Yuhan Li, Yishun Dou, Xuanhong Chen, Bingbing Ni, Yilin Sun, Yutian Liu, and Fuzhen Wang · 2023
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Diffrf: Rendering-guided 3d radiance field diffusion
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Yang Song, Prafulla Dhariwal, Mark Chen, and Ilya Sutskever · 2023
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Adding conditional control to text-to-image diffusion models
Lvmin Zhang, Anyi Rao, and Maneesh Agrawala · 2023
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Cat3d: Create anything in 3d with multi-view diffusion models
Ruiqi Gao*, Aleksander Holynski*, Philipp Henzler, Arthur Brussee, Ricardo Martin-Brualla, Pratul P. Srinivasan, Jonathan T. Barron, and Ben Poole* · 2024
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Genpc: Zero-shot point cloud completion via 3d generative priors
Mingqiang Wei An Li, Zhe Zu · 2025
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