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 <b>Combinatorial 3D Shape Dataset (2020)</b> [[Link]](https://github.com/POSTECH-CVLab/Combinatorial-3D-Shape-Generation)[[Paper]](https://arxiv.org/abs/2004.07414)
 <br>[Combinatorial 3D Shape Dataset](https://github.com/POSTECH-CVLab/Combinatorial-3D-Shape-Generation) is composed of 406 instances of 14 classes. Each object in our dataset is considered equivalent to a sequence of primitive placement. Compared to other 3D object datasets, our proposed dataset contains an assembling sequence of unit primitives. It implies that we can quickly obtain a sequential generation process that is a human assembling mechanism. Furthermore, we can sample valid random sequences from a given combinatorial shape after validating the sampled sequences. To sum up, the characteristics of our combinatorial 3D shape dataset are (i) combinatorial, (ii) sequential, (iii) decomposable, and (iv) manipulable.
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