Mar 29, 2022 · We propose 3DAttriFlow to disentangle and extract semantic attributes through different semantic levels in the input images.
This repository contains the code for the paper. 3D Shape Reconstruction from 2D Images with Disentangled Attribute Flow.
We propose the attribute flow pipe to explicitly disen- tangle the semantic attributes embedded in the global feature of 2D image, which can provide definite ...
3D Shape Reconstruction from 2D Images with Disentangled Attribute ...
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We propose 3DAttriFlow to disentangle and extract semantic attributes through different semantic levels in the input images.
We propose a novel deep network, named 3DAttri-. Flow, for reconstructing high-quality 3D shapes from single 2D images. Compared with the previous meth- ods, ...
The document proposes a method called 3DAttriFlow to disentangle and extract semantic attributes from 2D images to help with 3D shape reconstruction.
Reconstructing 3D shape from a single 2D image is a challenging task, which needs to estimate the detailed 3D structures based on the semantic attributes from ...
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Duration: 9:47
Posted: May 23, 2022
Posted: May 23, 2022
Aug 5, 2022 · We focus on the challenging task of extracting disentangled 3D attributes only from 2D image data. Specifically, we focus on human appearance.
3D Shape Reconstruction from 2D Images with Disentangled Attribute Flow, Point Cloud, CVPR 2022, Code · Pre-train, Self-train, Distill: A simple recipe for ...