Link paper and GitHub repository and add sample usage (#1)

- Link paper and GitHub repository and add sample usage (03a234ca0f0243a3de2895b1eaef34bcc8ae33d3)


Co-authored-by: Niels Rogge <nielsr@users.noreply.huggingface.co>

README.md

@@ -1,18 +1,18 @@
 ---
+language:
+- en
 license: cc-by-4.0
-language: [en]
 task_categories:
-  - image-to-image
-  - image-classification
-  - object-detection
-  - image-segmentation
-  - depth-estimation
+- image-to-image
 pretty_name: SCaN-TIR
 ---
 
-
 # SCaN-TIR: Stereo Clean-and-Noisy Paired Thermal Infrared Dataset
 
+[**TIDY: Thermal Infrared Image Denoising via Wavelet Domain Entropy and Directional Stripe Index**](https://huggingface.co/papers/2606.19813)
+
+[Code](https://github.com/williamrheeth/TIDY) | [Dataset](https://huggingface.co/datasets/williamrhee/SCaN-TIR) | [Video](https://youtu.be/PxcEG1ayDKE)
+
 SCaN-TIR is a real clean–noisy paired thermal infrared dataset for supervised TIR image denoising. It contains over 32.5K hardware-synchronized and geometrically aligned image pairs captured with two adjacent FLIR A65 thermal cameras, where one camera stream was intentionally degraded by disabling non-uniformity correction (NUC). The dataset includes both indoor and outdoor sequences at 640×512 resolution, providing real sensor noise rather than synthetic noise approximations.
 
 ## Highlights
@@ -26,9 +26,21 @@ SCaN-TIR is a real clean–noisy paired thermal infrared dataset for supervised
 * Provides both Fieldscale-mapped 8-bit images and original 14-bit images
 * Designed for supervised real-noise TIR denoising and downstream robotics perception
 
+## Usage
+
+You can download the dataset using the Hugging Face CLI:
+
+```bash
+pip install -U "huggingface_hub[cli]"
+
+huggingface-cli download williamrhee/SCaN-TIR \
+    --repo-type dataset \
+    --local-dir SCaN-TIR
+```
+
 ## Dataset Structure
 
-The dataset is organized into scene folders containing synchronized RGB and thermal infrared images.
+The dataset is organized into scene folders containing synchronized clean and noisy thermal infrared images.
 
 ```text
 SCaN-TIR
@@ -61,9 +73,4 @@ If you use SCaN-TIR in your research, please cite:
   year={2026},
   organization={IEEE}
 }
-```
-
-## Links
-
-* Project Repository: [TIDY GitHub Repository](https://github.com/williamrheeth/TIDY?utm_source=chatgpt.com)
-* Dataset Homepage: [SCaN-TIR Dataset](https://huggingface.co/datasets/williamrhee/SCaN-TIR?utm_source=chatgpt.com)
+```