PlankAssembly Dataset

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Dataset Summary

This is the dataset used for training PlankAssembly. It contains 26,707 shape programs derived from parametric CAD models.

Dataset Structure

PlankAssembly dataset is a directory with the following structure:

PlankAssemblyDataset
├── model               # shape program
|   └── <MODLE_ID>.json
└── splits              # dataset splits
    ├── train.txt
    ├── valid.txt
    └── test.txt

PlankAssembly DSL

A cabinet is typically assembled by a list of plank models, where each plank is represented as an axis-aligned cuboid. A cuboid has six degrees of freedom, which correspond to the starting and ending coordinates along the three axes:

Cuboid (x_min, y_min, z_min, x_max, y_max, z_max).

Each coordinate can either take a numerical value or be a pointer to the corresponding coordinate of another cuboid (to which it attaches to).

In the parametric modeling software, a plank is typically created by first drawing a 2D profile and then applying the extrusion command. Thus, we categorize the faces of each plank into sideface or endface, depending on whether they are along the direction of the extrusion or not. Then, given a pair of faces from two different planks, we consider that an attachment relationship exists if (i) the two faces are within a distance threshold of 1mm and (ii) the pair consists of one sideface and one endface.

Shape Program

Each shape program (model.json) is a JSON file with the following structure:

{
  # model id
  "name": str,
  # numerical values of all planks, the units are millimeters
  "planks": List[List],         # N x 6
  # extrusion direction of each plank
  "normal": List[List],         # N x 3
  # attachment relationships
  # -1 denotes no attachment relationship
  # Others denote the index of the flattened plank sequence
  "attach": List[List],         # N x 6
}

BibTex

Please cite our paper if you use PlankAssembly dataset in your work:

@inproceedings{PlankAssembly,
  author    = {Hu, Wentao and Zheng, Jia and Zhang, Zixin and Yuan, Xiaojun and Yin, Jian and Zhou, Zihan},
  title     = {PlankAssembly: Robust 3D Reconstruction from Three Orthographic Views with Learnt Shape Programs},
  booktitle = {ICCV},
  year      = {2023}
}