Add task categories, paper link, and project page

This PR updates the dataset card with:
- Task categories: `object-detection`, `image-segmentation`, and `robotics`.
- A link to the paper: [IndustryShapes: An RGB-D Benchmark dataset for 6D object pose estimation of industrial assembly components and tools](https://huggingface.co/papers/2602.05555).
- A link to the project page: [https://pose-lab.github.io/IndustryShapes](https://pose-lab.github.io/IndustryShapes).
- A summary of the dataset's purpose and structure based on the paper abstract.

README.md

@@ -1,4 +1,9 @@
 ---
+license: mit
+task_categories:
+- object-detection
+- image-segmentation
+- robotics
 dataset_info:
   features:
   - name: scene_id
@@ -45,5 +50,28 @@ configs:
     path: data/test-*
   - split: train
     path: data/train-*
-license: mit
----
+---
+
+# IndustryShapes
+
+[**Project Page**](https://pose-lab.github.io/IndustryShapes) | [**Paper**](https://huggingface.co/papers/2602.05555)
+
+IndustryShapes is a large-scale RGB-D benchmark dataset of industrial tools and components, designed for both instance-level and novel object 6D pose estimation. It bridges the gap between lab-based research and real-world industrial deployment by providing realistic scenes captured in industrial assembly settings.
+
+### Dataset Features
+Unlike traditional datasets focused on household products, IndustryShapes introduces five new object types with challenging properties. The dataset features:
+- **Realistic Settings:** Objects captured in authentic industrial assembly environments.
+- **Diverse Complexity:** Scenes ranging from simple to challenging, including single and multiple objects, as well as multiple instances of the same object.
+- **Unique Modalities:** It is the first dataset to offer RGB-D static onboarding sequences to support model-free and sequence-based approaches.
+- **Comprehensive Annotations:** Includes high-quality annotated poses, bounding boxes, and segmentation masks.
+
+### Dataset Organization
+The dataset is organized into two parts:
+- **Classic Set:** Includes a total of 4.6k images and 6k annotated poses.
+- **Extended Set:** Introduces additional data modalities for advanced evaluation of model-free and sequence-based methods.
+
+### Supported Tasks
+- **6D Object Pose Estimation** (Instance-level and Novel Object)
+- **Object Detection**
+- **Image Segmentation**
+- **Robotics**