Add project page to dataset card

README.md

@@ -1,81 +1,25 @@
 ---
-license: odc-by
+license: apache-2.0
 task_categories:
-- text-generation
-language:
-- en
-pretty_name: OLMo 2 Mix (November 2024)
-size_categories:
-- 1B<n<10B
-
-configs:
-  - config_name: default
-    data_files:
-      - split: train
-        path: data/*/*
-  - config_name: algebraic-stack
-    data_files:
-      - split: train
-        path: data/algebraic-stack/*      
-  - config_name: arxiv
-    data_files:
-      - split: train
-        path: data/arxiv/*  
-  - config_name: dclm
-    data_files:
-      - split: train
-        path: data/dclm/*  
-  - config_name: open-web-math
-    data_files:
-      - split: train
-        path: data/open-web-math/*      
-  - config_name: pes2o
-    data_files:
-      - split: train
-        path: data/pes2o/*   
-  - config_name: starcoder
-    data_files:
-      - split: train
-        path: data/starcoder/*  
-  - config_name: wiki
-    data_files:
-      - split: train
-        path: data/wiki/*  
-dataset_info:
-  features:
-  - name: id
-    dtype: string
-  - name: text
-    dtype: string
-  - name: added
-    dtype: string
-  - name: created
-    dtype: string
+- image-to-3d
+tags:
+- slam
+- 3d-reconstruction
+- monocular
 ---
 
-# OLMo 2 (November 2024) Pretraining set
-
-Collection of data used to train OLMo-2-1124 models. The majority of this dataset comes from DCLM-Baseline with no additional filtering, but we provide the explicit breakdowns below.
-
-| Name            | Tokens | Bytes (uncompressed) | Documents | License   |
-|-----------------|--------|----------------------|-----------|-----------|
-| DCLM-Baseline   | 3.70T  | 21.3TB               | 2.95B     | CC-BY-4.0 |
-| Arxiv           | 20.8B  | 77.2GB               | 3.95M     | ODC-BY    |
-| pes2o           | 58.6B  | 412GB                | 38M       | ODC-BY    |
-| starcoder       | 83.0B  | 458GB                | 78.7M     | ODC-BY    |
-| Algebraic-stack | 11.8B  | 44.0GB               | 2.83M     | ODC-BY    |
-| OpenWebMath     | 12.2B  | 47.23GB              | 2.89M     | ODC-BY    |
-| Wiki            | 3.66B  | 18.1GB               | 6.17M     | ODC-BY    |
-| Total           | 3.90T  | 22.4TB               | 3.08M     | ODC-BY    |
-
+This repository contains data for WildGS-SLAM: Monocular Gaussian Splatting SLAM in Dynamic Environments.
 
+[Paper](https://huggingface.co/papers/2504.03886) | [Project Page](https://wildgs-slam.github.io/) | [Code](https://github.com/GradientSpaces/WildGS-SLAM)
 
+WildGS-SLAM accurately tracks the camera trajectory and reconstructs a 3D Gaussian map for static elements from a monocular video sequence, effectively removing dynamic components.
 
-Please refer to the OLMo2 Tech Report for further details. 
 
-## Licensing Information
+### Datasets Used
 
-This **collection** is released under the **Open Data Commons Attribution License (ODC-By) v1.0** [license](https://opendatacommons.org/licenses/by/1-0/). The use of this dataset is also subject to [CommonCrawl's Terms of Use](https://commoncrawl.org/terms-of-use).
+WildGS-SLAM uses data from the following datasets:
 
-## Citation
-A technical manuscript is forthcoming!
+* **Wild-SLAM Mocap Dataset:** ([Hugging Face](https://huggingface.co/datasets/gradient-spaces/Wild-SLAM/tree/main/Mocap))  Download instructions are available in the [github repository](https://github.com/GradientSpaces/WildGS-SLAM).
+* **Wild-SLAM iPhone Dataset:** ([Hugging Face](https://huggingface.co/datasets/gradient-spaces/Wild-SLAM/tree/main/iPhone)) Download instructions are available in the [github repository](https://github.com/GradientSpaces/WildGS-SLAM).
+* **Bonn Dynamic Dataset:** ([Website](https://www.ipb.uni-bonn.de/data/rgbd-dynamic-dataset/index.html)) Download instructions are available in the [github repository](https://github.com/GradientSpaces/WildGS-SLAM).
+* **TUM RGB-D (dynamic) Dataset:** Download instructions are available in the [github repository](https://github.com/GradientSpaces/WildGS-SLAM).