SDFusion: Multimodal 3D Shape Completion, Reconstruction, and Generation-Reference-Cited by-同舟云学术

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SDFusion: Multimodal 3D Shape Completion, Reconstruction, and Generation

Published:2023-06 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
language:
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Author:

Cheng Yen-Chi¹,Lee Hsin-Ying²,Tulyakov Sergey²,Schwing Alexander¹,Gui Liangyan¹

Affiliation:

1. University of Illinois Urbana-Champaign

2. Snap Research

Funder

NSF

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10203037/10203050/10203360.pdf?arnumber=10203360

Reference53 articles.

1. Diffusion models beat gans on image synthesis;dhariwal;NeurIPS,0

2. Bert: Pretraining of deep bidirectional transformers for language understanding;devlin;NAACL,0

3. Denoising diffusion probabilistic models;ho;NeurIPS,2020

4. Stylenerf: A style-based 3d-aware generator for high-resolution image synthesis;gu;ICLRE,0

5. 3D Shape Generation and Completion through Point-Voxel Diffusion

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