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autonomousvision / occupancy_networks

This repository contains the code for the paper "Occupancy Networks - Learning 3D Reconstruction in Function Space"
https://avg.is.tuebingen.mpg.de/publications/occupancy-networks
MIT License
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How long do you train your model on ShapeNet? #85

Open aidendef opened 3 years ago

aidendef commented 3 years ago

I am trying to train the onet model from the beginning in shapenet dataset.

method: onet data: path: data/ShapeNet img_folder: img_choy2016 img_size: 224 points_subsample: 2048 model: encoder_latent: null decoder: cbatchnorm encoder: resnet18 c_dim: 256 z_dim: 0 training: out_dir: out/img/onet batch_size: 64 model_selection_metric: iou model_selection_mode: maximize visualize_every: 20000 validate_every: 20000 test: threshold: 0.2 eval_mesh: true eval_pointcloud: false generation: batch_size: 100000 refine: false n_x: 128 n_z: 1 resolution_0: 32 upsampling_steps: 2

Given the above assumptions, how long does the epoch have to proceed to a level similar to that presented in the paper? I can't find any epoch or time about training time in the paper and supplementary material. Is it correct that the previously provided code(onet.yaml) provides the best performance?

novauto-nju commented 3 years ago

Have you found any information about epoch？My epoch=110, but the program didn't stop