3d image generation
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Visual Object Networks: Image Generation with Disentangled 3D
images of objects with a disentangled 3D representation. Inspired by classic on generating images in 2D ignoring the 3D nature of the world. |
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Synthetic Lung Nodule 3D Image Generation Using Autoencoders
9 sept. 2019 Index Terms—Lung nodules CT scan |
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Feature preserving Delaunay mesh generation from 3D multi
3 sept. 2009 The idea is to explicitly sample corners and edges from the input image and to constrain the Delaunay refinement algorithm to preserve these ... |
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Mesh generation from 3D multi-material images
28 sept. 2009 Mesh generation from 3D multi-material images. MICCAI 2009 - 12th International Medical Image Computing and Computer-Assisted Inter-. |
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GRAM: Generative Radiance Manifolds for 3D-Aware Image
Learning 3D-aware image generation with Generative. Adversarial Networks (GAN) [17] has attracted a surge of attention in recent years [10–1221 |
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Disentangled and Controllable Face Image Generation via 3D
Disentangled and Controllable Face Image Generation via 3D. Imitative-Contrastive Learning. Yu Deng*12. Jiaolong Yang2. Dong Chen2. Fang Wen2. Xin Tong2. |
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Fluoroscopic 3D Image Generation from Patient-Specific PCA
18 janv. 2022 Fluoroscopic 3D Image Generation from Patient-Specific PCA Motion. Models Derived from 4D-CBCT. Patient Datasets: A Feasibility Study. |
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AtlasNet: A Papier-Mâché Approach to Learning 3D Surface
27 févr. 2018 Given input as either a 2D image or a 3D point cloud (a) we automatically generate a corresponding 3D mesh (b) and its atlas. |
| Inverse Graphics GAN: Learning to Generate 3D Shapes from |
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StyleSDF: High-Resolution 3D-Consistent Image and Geometry
We achieve this by merging a SDF-based 3D representation with a style-based 2D generator. Our 3D implicit network renders low-resolution feature maps from |
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Visual Object Networks: Image Generation with Disentangled 3D
images of objects with a disentangled 3D representation Inspired by classic on generating images in 2D, ignoring the 3D nature of the world As a result, they |
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3d Image Generation from Single 2d Image using Monocular Depth
15 déc 2019 · Similarly 3D effect can also be created by parallax effect by taking two images and layering them one over the other A 3D image can be captured |
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HoloGAN: Unsupervised Learning of 3D - CVF Open Access
Most generative models rely on 2D kernels to generate images and make few assumptions about the 3D world These models therefore tend to create blurry |
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Pixel2Mesh: Generating 3D Mesh Models from Single RGB Images
achieved for 3d shape generation from a single color image using deep learning tech- niques [6, 9] Taking advantage of convolutional layers on regular grids or |
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Improved Adversarial Systems for 3D Object Generation and
3D-IWGAN can be applied to reconstructing 3D shape from 2D images by integrating our training with a Variational Auto-Encoder (VAE) [5] This leads to our new |
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Structure-Aware 3D Shape Synthesis from Single-View Images
In order to learn the deep generative models for cross-view image synthesis, we generate aligned object images from multiple viewpoints through projecting 3D |
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