GeBiD (Geometric shapes Bimodal Dataset)
Introduced by Sejnova et al. in Benchmarking Multimodal Variational Autoencoders: CdSprites+ Dataset and Toolkit
We provide a custom synthetic bimodal dataset, called GeBiD, designed specifically for the comparison of the joint- and cross-generative capabilities of Multimodal Variational Autoencoders. It comprises RGB images of geometric primitives and textual descriptions. The dataset offers 5 levels of difficulty (based on the number of attributes) to find the minimal functioning scenario for each model. Moreover, its rigid structure enables automatic qualitative evaluation of the generated samples.
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