Add paper and GitHub links, update citation and metadata (#1)

- Add paper and GitHub links, update citation and metadata (066c210e9f5271f3ac8c9142aca85cb421c36d44)


Co-authored-by: Niels Rogge <nielsr@users.noreply.huggingface.co>

README.md

@@ -1,61 +1,59 @@
 ---
 license: cc-by-nc-4.0
-modalities:
-  - image
+size_categories:
+- 10K<n<100K
 task_categories:
-  - image-segmentation
+- image-segmentation
+modalities:
+- image
 tags:
-  - synthetic
-size_categories:
-  - 10K<n<100K
-
-arxiv:
-
+- synthetic
+- robotics
 ---
 
 # TransFrag27K: Transparent Fragment Dataset
 
+[**Paper**](https://huggingface.co/papers/2603.20290) | [**Code**](https://github.com/Keithllin/Transparent-Fragments-Contour-Estimation)
+
+**Authors:** Qihao Lin, Borui Chen, Yuping Zhou, Jianing Wu, Yulan Guo, Weishi Zheng, Chongkun Xia.
+
 ## Dataset Summary
 TransFrag27K is the first large-scale transparent fragment dataset, which contains **27,000 images and masks** at a resolution of 640×480. The dataset covers fragments of common everyday glassware and incorporates **more than 150 background textures** and **100 HDRI environment lightings**.  
 
 <p align="center">
-  <img src="./demonstration.png" alt="Demonstration" width="1000"/>
+  <img src="https://huggingface.co/datasets/chenbr7/TransFrag27K/resolve/main/demonstration.png" alt="Demonstration" width="1000"/>
 </p>
 
-
 Transparent objects, being a special category, have refractive and transmissive material properties that make their visual features highly sensitive to environmental lighting and background. In real-world scenarios, collecting data of transparent objects with diverse backgrounds and lighting conditions is challenging, and annotations are prone to errors due to difficulties in recognition.  
 
-To address this, we designed an **automated dataset generation pipeline in Blender**:  
+To address this, the authors designed an **automated dataset generation pipeline in Blender**:  
 - Objects are randomly fractured using the Cell Fracture add-on.  
 - Parametric scripts batch-adjust lighting, backgrounds, and camera poses.  
 - Rendering is performed automatically to output paired RGB images and binary masks.  
 
-The Blender script we used to generate TransFrag27k also supports batch dataset generation with any scene in which objects are placed at a horizontal plane. For implementation details, please refer to:  
-[Transparent-Fragments-Contour-Estimation](https://github.com/Keithllin/Transparent-Fragments-Contour-Estimation)  
-
+The Blender script used to generate TransFrag27k also supports batch dataset generation with any scene in which objects are placed at a horizontal plane. For implementation details, please refer to the [official GitHub repository](https://github.com/Keithllin/Transparent-Fragments-Contour-Estimation).  
 
 ---
 
 ## Supported Tasks
 - Semantic Segmentation for various transparent fragments.
+- Contour estimation for autonomous reassembly.
 
 ---
 
-
 ## Dataset Structure
 In our released dataset, to facilitate subsequent customized processing, we organize each object’s data in the following structure:  
 
-```├─TransFrag27K
+```
+├─TransFrag27K
 │ ├─Planar1
 │ │ ├─anno_mask
 │ │ └─rgb
 │ ├─Planar2
-
 │ │ ├─anno_mask
 │ │ └─rgb
 │ ├─Curved1
 │ │ ├─anno_mask
-
 │ │ └─rgb
 │ ├─Curved2
 │ │ ├─anno_mask
@@ -71,7 +69,6 @@ In our released dataset, to facilitate subsequent customized processing, we orga
 │ │ └─rgb
 ```
 
-
 We mainly organize the dataset according to the **shape classes** of transparent fragments:  
 - **Planar**  
   Mainly includes fragments from flat regions such as dish bottoms and glass bases.  
@@ -84,11 +81,15 @@ We mainly organize the dataset according to the **shape classes** of transparent
 
 ## Citation
 If you find this dataset or the associated work useful for your research, please cite the paper:
-```
-@article{lin2025transparent,
-  title={Transparent Fragments Contour Estimation via Visual-Tactile Fusion for Autonomous Reassembly},
-  author=
-  year=
 
+```bibtex
+@misc{lin2026transparentfragmentscontourestimation,
+      title={Transparent Fragments Contour Estimation via Visual-Tactile Fusion for Autonomous Reassembly}, 
+      author={Qihao Lin and Borui Chen and Yuping Zhou and Jianing Wu and Yulan Guo and Weishi Zheng and Chongkun Xia},
+      year={2026},
+      eprint={2603.20290},
+      archivePrefix={arXiv},
+      primaryClass={cs.CV},
+      url={https://arxiv.org/abs/2603.20290}, 
 }
 ```