Update paper link and metadata

README.md

@@ -1,14 +1,14 @@
 ---
+language:
+- en
 license: cc-by-4.0
+size_categories:
+- n<1K
 task_categories:
 - depth-estimation
-language:
-- en
+pretty_name: D2P
 tags:
 - monocular-depth-estimation-evaluation
-pretty_name: D2P
-size_categories:
-- n<1K
 dataset_info:
   features:
   - name: image
@@ -59,12 +59,12 @@ configs:
   - split: evaluation
     path: data/evaluation-*
 ---
----
+
 # The D2P dataset
 
 The **D2P dataset** is a dataset based on the Depth2Pose monocular depth estimation benchmark, a pose-based evaluation of MDEs without ground-truth depth. The dataset contains challenging scenes beyond the distribution of common training data, together with a simple and extensible evaluation framework, presented on the github page. The scenes are divided into two categories: statues and vegetation. Undistorted images and reconstructions in standard colmap format is provided for each scene, together with a list of image pairs used for the evaluation.
 
-[**paper** (coming later)]()  |  [**github**](https://github.com/kocurvik/depth2pose)  |  [**webpage**](https://kocurvik.github.io/depth2pose/) 
+[**Paper**](https://huggingface.co/papers/2605.19797)  |  [**GitHub**](https://github.com/kocurvik/depth2pose)  |  [**Webpage**](https://kocurvik.github.io/depth2pose/) 
 
 ## Dataset Structure
 
@@ -103,7 +103,7 @@ Each **scene** contains:
   - 3D points
   - rigs
 - `scene1_image_list.txt`: List of all images used for the benchmark, found in the images/ folder 
-- `scene1_image_pairs.txt`: List of all image pairs used for the benchmark, for which realtive pose is evaluated
+- `scene1_image_pairs.txt`: List of all image pairs used for the benchmark, for which relative pose is evaluated
 
 ### Direct Use
 
@@ -115,12 +115,12 @@ Benchmarking monocular depth estimators. For the current leaderboard, see the [D
 from datasets import load_dataset
 
 ds = load_dataset("floodgab/d2p_dataset")
-print(ds["validation"][0])
+print(ds["evaluation"][0])
 ```
 
 ### Loading Example
 
-To download the Depth2Pose dataset
+To download the Depth2Pose dataset:
 
 ```python
 from huggingface_hub import snapshot_download
@@ -129,7 +129,7 @@ path = snapshot_download("floodgab/d2p_dataset")
 ```
 
 ## Citation
-If you use Depth2Pose in your research or find our work helpful, please cite
+If you use Depth2Pose in your research or find our work helpful, please cite:
 ```bibtex
 @misc{depth2pose,
   title={{Depth2Pose}: A Pose-Based Benchmark for Monocular Depth Estimation without Ground-Truth Depth},