RC-49 is a benchmark dataset for generating images conditional on a continuous scalar variable. It is made by rendering 49 3-D chair models from ShapeNet individually. Each chair model is rendered at 899 yaw angles from $0.1^{\circ}$ to $89.9^{\circ}$ with a stepsize of $0.1^{\circ}$. This dataset contains 44,051 RGB images of size $64\times64$ with corresponding yaw angles as labels.
Note that in CcGAN, angles are used for training if their last digits are odd. Thus, there are 450 angles in the training set. Moreover, for these 450 training angles, only 25 images for each angle are used for the training.
Variants: RC-49
This dataset is used in 1 benchmark:
| Task | Model | Paper | Date |
|---|---|---|---|
| Image Generation | cDR-RS | Efficient Subsampling of Realistic Images … | 2021-03-20 |
| Image Generation | CcGAN (SVDL+ILI) | Continuous Conditional Generative Adversarial Networks: … | 2020-11-15 |
Recent papers with results on this dataset: