Improve model card: Add pipeline tag, paper, and code links for Talking Points

This PR enriches the model card for "Talking Points: Describing and Localizing Pixels" by:

- Adding the `pipeline_tag: keypoint-detection` to improve discoverability on the Hugging Face Hub, as the model focuses on pixel-level grounding and keypoint localization.
- Populating the model card content with a clear description based on the paper's abstract and the GitHub README.
- Including the project's teaser image for visual context.
- Providing a direct link to the research paper: [Talking Points: Describing and Localizing Pixels](https://huggingface.co/papers/2510.14583).
- Adding a link to the official GitHub repository for code and further details: `https://github.com/matanr/Talking_Points`.
- Retaining the existing license and incorporating the acknowledgments from the GitHub README.

Please review and merge if these updates meet the requirements.

README.md

@@ -1,3 +1,26 @@
----
-license: apache-2.0
----
+---
+license: apache-2.0
+pipeline_tag: keypoint-detection
+---
+
+# Talking Points: Describing and Localizing Pixels
+
+This repository contains the official implementation of the **Talking Points** framework, presented in the paper [Talking Points: Describing and Localizing Pixels](https://huggingface.co/papers/2510.14583).
+
+Vision-language models have achieved remarkable success in cross-modal understanding, but often remain limited to object-level or region-level grounding, lacking the capability for pixel-precise keypoint comprehension through natural language. Talking Points introduces a novel framework for pixel-level grounding, consisting of two complementary components:
+-   A **Point Descriptor** that generates rich, contextual descriptions of individual keypoints.
+-   A **Point Localizer** that regresses precise pixel coordinates from these descriptions.
+
+Unlike prior work that relies on templated prompts or keypoint names, our approach produces free-form, coarse-to-fine descriptions that situate keypoints within their visual context.
+
+<div align="center">
+  <img src="https://github.com/matanr/Talking_Points/raw/master/images/teaser.png" width="100%"/>
+</div>
+
+For more detailed information, including installation instructions, dataset creation, training scripts, and evaluation protocols, please refer to the [official GitHub repository](https://github.com/matanr/Talking_Points).
+
+## Acknowledgments
+This repository is built upon and incorporates code from [OMG-Seg and OMG-LLaVA](https://github.com/lxtGH/OMG-Seg/tree/main). In addition, it uses the code from [LLaVA](https://github.com/haotian-liu/LLaVA).
+
+## License
+This project follows the [Apache-2.0 license](https://github.com/haotian-liu/LLaVA?tab=Apache-2.0-1-ov-file), for the respect of both [LLaVA](https://github.com/haotian-liu/LLaVA) and [XTuner](https://github.com/InternLM/xtuner) codebase.