Update dataset card for SpatialEdit-500K

README.md

@@ -1,24 +1,35 @@
 ---
 license: apache-2.0
+task_categories:
+- image-to-image
 ---
 
 # SpatialEdit-500K
 
-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, camera viewpoint change.
+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 is released as part of the **SpatialEdit** project and is generated with a controllable rendering pipeline to provide structured spatial transformations at scale.
+The dataset was introduced in the paper [SpatialEdit: Benchmarking Fine-Grained Image Spatial Editing](https://huggingface.co/papers/2604.04911). It is generated with a controllable rendering pipeline to provide structured spatial transformations at scale.
 
-## Highlights
-
-- Large-scale synthetic data for spatially grounded image editing
-- Covers both object-centric and camera-centric transformations
-- Used to train the SpatialEdit baseline model
+## Project Resources
 
-## Project Links
+- **GitHub Repository:** [EasonXiao-888/SpatialEdit](https://github.com/EasonXiao-888/SpatialEdit)
+- **Model:** [SpatialEdit-16B](https://huggingface.co/EasonXiao-888/SpatialEdit-16B)
+- **Benchmark:** [SpatialEdit-Bench](https://huggingface.co/datasets/EasonXiao-888/SpatialEdit-Bench)
 
-- Paper: https://arxiv.org/pdf/2604.04911
-- GitHub: https://github.com/EasonXiao-888/SpatialEdit
-- Model: https://huggingface.co/EasonXiao-888/SpatialEdit-16B
-- Benchmark: https://huggingface.co/datasets/EasonXiao-888/SpatialEdit-Bench
+## Highlights
 
-Please visit the GitHub repository for code, demo, and additional project details:
+- **Large-scale synthetic data:** 500,000 samples for spatially grounded image editing.
+- **Comprehensive transformations:** Covers both object-centric (moving, rotation) and camera-centric transformations.
+- **High fidelity:** Generated with a controllable Blender pipeline rendering objects across diverse backgrounds with systematic camera trajectories.
+- **Precise labels:** Provides precise ground-truth transformations for spatial manipulation tasks.
+
+## Citation
+
+```bibtex
+@article{xiao2026spatialedit,
+  title   = {SpatialEdit: Benchmarking Fine-Grained Image Spatial Editing},
+  author  = {Xiao, Yicheng and Zhang, Wenhu and Song, Lin and Chen, Yukang and Li, Wenbo and Jiang, Nan and Ren, Tianhe and Lin, Haokun and Huang, Wei and Huang, Haoyang and Li, Xiu and Duan, Nan and Qi, Xiaojuan},
+  journal = {arXiv preprint arXiv:2604.04911},
+  year    = {2026}
+}
+```