3D-aware Conditional Image Synthesis

Kangle Deng; Gengshan Yang; Deva Ramanan; Jun-Yan Zhu

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arXiv · 2302.08509

3D-aware Conditional Image Synthesis

Kangle Deng·Gengshan Yang·Deva Ramanan·Jun-Yan Zhu

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Abstract

We propose pix2pix3D, a 3D-aware conditional generative model for controllable photorealistic image synthesis. Given a 2D label map, such as a segmentation or edge map, our model learns to synthesize a corresponding image from different viewpoints. To enable explicit 3D user control, we extend conditional generative models with neural radiance fields. Given widely-available monocular images and label map pairs, our model learns to assign a label to every 3D point in addition to color and density, which enables it to render the image and pixel-aligned label map simultaneously. Finally, we build an interactive system that allows users to edit the label map from any viewpoint and generate outputs accordingly.

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Kangle Deng, Gengshan Yang, Deva Ramanan, Jun-Yan Zhu. 2023-02-16. 3D-aware Conditional Image Synthesis. https://arxiv.org/abs/2302.08509

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