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This repository contains the code for the paper "Occupancy Networks - Learning 3D Reconstruction in Function Space"

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Occupancy Networks

Several attempts to improve the performance of ONet on the task of single-image reconstruction.

Currently, by introducing depth map & local feature extraction into the single-image reconstruction pipeline, the mesh_iou (evaluated on the original 100000 points) can achieve 65.1%, which is better than 59.7% from the original ONet. The reconstructions are also visually better.

I'm trying hard to write a paper for these contributions :).

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This repository contains the code for the paper "Occupancy Networks - Learning 3D Reconstruction in Function Space"

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  • Python 70.1%
  • C++ 11.0%
  • Cuda 10.5%
  • C 4.2%
  • Mako 2.0%
  • Objective-C 1.3%
  • Shell 0.9%