PartNet: A Large-scale Benchmark for Fine-grained and Hierarchical Part-level 3D Object Understanding

This repository contains code and scripts for PartNet segmentation experiments in Section 5.

About this repository

    data/
        sem_seg_h5/                 # the train/val/test data for Sec 5.1
        ins_seg_h5/                 # an intermediate data format for Sec 5.3
        ins_seg_h5_for_detection/   # the train/val data for our proposed method in Sec 5.3
        ins_seg_h5_for_sgpn/        # the train/val data for SGPN baseline in Sec 5.3
        ins_seg_h5_gt/              # the ground-truth test data in Sec 5.3
    exps/
        sem_seg_pointcnn            # the code for PointCNN baseline in Sec 5.1
        ins_seg_detection/          # the code for our proposed method in Sec 5.3
        ins_seg_sgpn/               # the code for SGPN baseline in Sec 5.3
        utils/                      # some utility functions
        tf_ops/                     # some customized Tensorflow layers (you may need to re-compile them on your machine)
    stats/
        all_valid_anno_info.txt         # Store all valid PartNet Annotation meta-information
                                        # <anno_id, version_id, category, shapenet_model_id, annotator_id>
        before_merging_label_ids/       # Store all expert-defined part semantics before merging
            Chair.txt
            ...
        merging_hierarchy_mapping/      # Store all merging criterion
            Chair.txt
            ...
        after_merging_label_ids/        # Store the part semantics after merging
            Chair.txt                   # all part semantics
            Chair-hier.txt              # all part semantics that are selected for Sec 5.2 experiments
            Chair-level-1.txt           # all part semantics that are selected for Sec 5.1 and 5.3 experiments for chair level-1
            Chair-level-2.txt           # all part semantics that are selected for Sec 5.1 and 5.3 experiments for chair level-2
            Chair-level-3.txt           # all part semantics that are selected for Sec 5.1 and 5.3 experiments for chair level-3
            ...
        train_val_test_split/           # An attemptive train/val/test splits (may be changed for official v1 release and PartNet challenges)
            Chair.train.json
            Chair.val.json
            Chair.test.json

Dataset Repo

Please check the dataset repo for downloading the dataset and helper scripts for data usage.

Cite

@InProceedings{Mo_2019_CVPR,
    author = {Mo, Kaichun and Zhu, Shilin and Chang, Angel X. and Yi, Li and Tripathi, Subarna and Guibas, Leonidas J. and Su, Hao},
    title = {{PartNet}: A Large-Scale Benchmark for Fine-Grained and Hierarchical Part-Level {3D} Object Understanding},
    booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
    month = {June},
    year = {2019}
}

Questions

Please post issues for questions and more helps on this Github repo page. For data annotation error, please fill in this errata.

License

MIT Licence