DisCoScene: Spatially Disentangled Generative Radiance Fields for Controllable 3D-aware Scene Synthesis

Author:

Xu Yinghao1,Chai Menglei2,Shi Zifan3,Peng Sida4,Skorokhodov Ivan5,Siarohin Aliaksandr2,Yang Ceyuan1,Shen Yujun1,Lee Hsin-Ying2,Zhou Bolei6,Tulyakov Sergey2

Affiliation:

1. CUHK

2. Snap Inc.

3. HKUST

4. ZJU

5. KAUST

6. UCLA

Publisher

IEEE

Reference68 articles.

1. Bungeenerf: Progressive neural radiance field for extreme multi-scale scene rendering;xiangli;Eur Conf Comput Vis,0

2. Detail Me More: Improving GAN’s photo-realism of complex scenes

3. Object-compositional neural implicit surfaces;wu;Eur Conf Comput Vis,0

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1. Car-Studio: Learning Car Radiance Fields From Single-View and Unlimited In-the-Wild Images;IEEE Robotics and Automation Letters;2024-03

2. A Survey on Deep Generative 3D-aware Image Synthesis;ACM Computing Surveys;2023-11-09

3. Set-the-Scene: Global-Local Training for Generating Controllable NeRF Scenes;2023 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW);2023-10-02

4. 3DAvatarGAN: Bridging Domains for Personalized Editable Avatars;2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR);2023-06

5. SDFusion: Multimodal 3D Shape Completion, Reconstruction, and Generation;2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR);2023-06

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