Improve dataset card: add task categories and links to paper and code

Hi! I'm Niels from the Hugging Face community science team. I noticed this dataset is part of the "RobustSpring" paper. This PR improves the dataset card by:
- Adding the `task_categories` to the metadata (`depth-estimation` and `other`).
- Linking the README to the official [Hugging Face paper page](https://huggingface.co/papers/2505.09368).
- Adding a link to the associated GitHub repository for data generation tools.
- Updating the citation section with the latest paper info.

README.md

@@ -1,5 +1,12 @@
 ---
+language:
+- en
 license: cc-by-4.0
+size_categories:
+- 100K<n<1M
+task_categories:
+- depth-estimation
+- other
 dataset_info:
   features:
   - name: image1_path
@@ -35,8 +42,6 @@ configs:
   data_files:
   - split: test
     path: data/test-*
-language:
-- en
 tags:
 - computer-vision
 - robustness
@@ -44,23 +49,17 @@ tags:
 - optical-flow
 - scene-flow
 - stereo
-size_categories:
-- 100K<n<1M
 ---
 
 # RobustSpring: Benchmarking Robustness to Image Corruptions for Optical Flow, Scene Flow and Stereo
 
+[Paper](https://huggingface.co/papers/2505.09368) | [Project Page](https://spring-benchmark.org) | [Code](https://github.com/cv-stuttgart/sceneflow_from_blender)
+
 This dataset provides structured **metadata only** for the [RobustSpring](https://spring-benchmark.org) dataset. All image samples are referenced by relative file paths, and must be paired with local image data downloaded separately from the public release site.
 
 * **Dataset on the Hub**: [jeschmalfuss/RobustSpring](https://huggingface.co/datasets/jeschmalfuss/RobustSpring)
-* **Image Data**: [RobustSpring](https://doi.org/10.18419/DARUS-5047)
+* **Image Data**: [RobustSpring (DARUS)](https://doi.org/10.18419/DARUS-5047)
 
-For the related [research](https://www.arxiv.org/abs/2505.09368) see
-```
-RobustSpring: Benchmarking Robustness to Image Corruptions for Optical Flow, Scene Flow and Stereo
-Jenny Schmalfuss*, Victor Oei*, Lukas Mehl, Madlen Bartsch, Shashank Agnihotri, Margret Keuper, Andrés Bruhn
-https://doi.org/10.48550/arXiv.2505.09368
-```
 RobustSpring is an image-corruption dataset for optical flow, scene flow and stereo, that applies 20 different image corruption to the test split of the [Spring](https://spring-benchmark.org) dataset.
 The combined Spring and RobustSpring website is at [spring-benchmark.org](https://spring-benchmark.org)
 
@@ -161,7 +160,7 @@ from datasets import load_dataset
 dataset = load_dataset("jeschmalfuss/RobustSpring", split="test")  # all samples
 ```
 
-## 3. Filtering by Data Type
+### 3. Filtering by Data Type
 
 You can filter the dataset to only retrieve the type of samples you're interested in: optical flow, scene flow or stereo.
 
@@ -185,10 +184,28 @@ img1 = Image.open(os.path.join(base_path, sample["image1_path"]))
 img2 = Image.open(os.path.join(base_path, sample["image2_path"]))
 ```
 
-
 ---
 
+## Citation
+
+If you use this dataset, please cite the following papers:
+
+```bibtex
+@article{schmalfuss2025robustspring,
+  title={RobustSpring: Benchmarking Robustness to Image Corruptions for Optical Flow, Scene Flow and Stereo},
+  author={Schmalfuss, Jenny and Oei, Victor and Mehl, Lukas and Bartsch, Madlen and Agnihotri, Shashank and Keuper, Margret and Bruhn, Andr{\\'e}s},
+  journal={arXiv preprint arXiv:2505.09368},
+  year={2025}
+}
+
+@InProceedings{Mehl2023_Spring,
+    author    = {Lukas Mehl and Jenny Schmalfuss and Azin Jahedi and Yaroslava Nalivayko and Andr\'es Bruhn},
+    title     = {Spring: A High-Resolution High-Detail Dataset and Benchmark for Scene Flow, Optical Flow and Stereo},
+    booktitle = {Proc. IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
+    year      = {2023}
+}
+```
 
 ## License
 
-The RobustSpring dataset is licensed under CC-BY-4.0
+The RobustSpring dataset is licensed under CC-BY-4.0