FlyingThings3D is a synthetic dataset for optical flow, disparity and scene flow estimation. It consists of everyday objects flying along randomized 3D trajectories. We generated about 25,000 stereo frames with ground truth data. Instead of focusing on a particular task (like KITTI) or enforcing strict naturalism (like Sintel), we rely on randomness and a large pool of rendering assets to generate orders of magnitude more data than any existing option, without running a risk of repetition or saturation.
Variants: FlyingThings3D
This dataset is used in 1 benchmark:
| Task | Model | Paper | Date |
|---|---|---|---|
| 10-shot image generation | 1 | 0/1 Deep Neural Networks via … | 2022-06-19 |
Recent papers with results on this dataset: