SpatialEdit-500K is a synthetic training dataset for fine-grained image spatial editing. It is built for learning geometry-aware edits such as object moving, object rotation, and camera viewpoint change.
The dataset was introduced in the paper SpatialEdit: Benchmarking Fine-Grained Image Spatial Editing. It is generated with a controllable rendering pipeline to provide structured spatial transformations at scale.
GitHub Repository:… See the full description on the dataset page:
https://huggingface.co/datasets/EasonXiao-888/SpatialEdit-500K.
