In this paper, we propose 3D-Mask-GAN, a novel framework to efficiently accomplish the task of unsupervised single-view 3D object reconstruction.
We use 3D Generative Adversarial Networks (GAN) to predict the 3D shape from the single-view image and improve reconstruction accuracy by applying 2D projection ...
3D-Mask-GAN, a novel framework to efficiently accomplish the task of unsupervised single-view 3D object reconstruction and improve reconstruction accuracy.
In this paper, we propose 3D-. Mask-GAN, a novel framework to efficiently accomplish the task of unsupervised single-view 3D object reconstruction. We use. 3D ...
There are several image-based approaches to reconstructing real objects as 3D models, e.g., those based on photogrammetry [6,7] and new technologies such as ...
Our approach leverages StyleGAN-generated multi-view pseudo images to learn a 3D model without 3D supervision, which can perform single-view 3D reconstruction ...
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Jul 20, 2022 · Recent research has shown that controllable image generation based on pre-trained GANs can benefit a wide range of computer vision tasks.
Missing: Mask- | Show results with:Mask-
We found that such a pre-trained GAN indeed contains rich 3D knowledge and thus can be used to recover 3D shape from a single 2D image in an unsupervised ...
Jul 20, 2022 · Recent research has shown that controllable image generation based on pre-trained GANs can benefit a wide range of computer vision tasks.
Specifically, our framework finds the latent code of the pre-trained 3D GAN that best recovers the 3D object in accordance with the single-view observation.