Update README.md

README.md

@@ -11,38 +11,44 @@ tags:
 - robotics
 ---
 
-# TransFrag27K: Transparent Fragment Dataset
+# TransFrag27K: Transparent Fragments Dataset
+
+[![arXiv](https://img.shields.io/badge/arXiv-2603.20290-b31b1b.svg)](https://arxiv.org/abs/2603.20290)
+
+## Paper
+[**Transparent Fragments Contour Estimation via Visual-Tactile Fusion for Autonomous Reassembly**](https://arxiv.org/abs/2603.20290) 
+
+
+[**Code**](https://github.com/Keithllin/Transparent-Fragments-Contour-Estimation)
 
-[**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**.  
+TransFrag27K is the first large-scale transparent fragments 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="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.  
+## Automated Synthetic Dataset Generation
+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 fragments is challenging because they are difficult to perceive and exhibit highly diverse and random shapes, which makes accurate annotation prone to errors.
 
-To address this, the authors designed an **automated dataset generation pipeline in Blender**:  
+To address this, we 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 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).  
+ The Blender pipeline used to generate TransFrag27K is generalizable to arbitrary objects placed on a horizontal plane (e.g., tabletop or ground scenarios), with randomized camera viewpoints and adjustable environmental configurations. For implementation details, please refer to our [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:  
+In our released dataset, to facilitate subsequent customized processing, we organize each category’s data in the following structure:  
 
 ```
 ├─TransFrag27K