chexenia / PrimitiveNet

PrimitiveNet: Primitive Instance Segmentation with Local Primitive Embedding under Adversarial Metric (ICCV 2021)

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PrimitiveNet

Source code for the paper:

Jingwei Huang, Yanfeng Zhang, Mingwei Sun. [PrimitiveNet: Primitive Instance Segmentation with Local Primitive Embedding under Adversarial Metric], ICCV 2021 .

PrimitiveNet Teaser

Compile

git submodule update --init --recursive
sh scripts/compile.sh

Download data and checkpoints

Follow the comments in download.sh to download the data and checkpoints.

sh scripts/download.sh

Evaluation on ABC

sh scripts/evaluate.sh

Predicted results on test set are visualized in src/results/visualize. Original network predictions are saved in src/results/predictions.

After all test set predictions are generated, an evaluation for mSegIOU/mLabelIOU/APs will be executed and final results will be saved at src/results/statistics.

Train ABC from scratch

sh scripts/train.sh

Logs and trained models will be saved at src/results/checkpoint.

Execute on a large scene

sh scripts/test_scene.sh

The segmented large scene is stored at src/results/visualize/final.obj.

About

PrimitiveNet: Primitive Instance Segmentation with Local Primitive Embedding under Adversarial Metric (ICCV 2021)

License:MIT License


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Language:Python 60.8%Language:C++ 23.7%Language:Cuda 9.6%Language:C 3.5%Language:CMake 1.5%Language:Shell 0.9%