Update README.md

README.md

@@ -94,6 +94,8 @@ size_categories:
 This is the version of the SelvaBox dataset that has been pre-processed and presented in our SelvaBox paper.
 The dataset is made of 14 rasters resampled at 4.5 cm GSD, from three different countries: Brazil, Ecuador and Panama. These rasters were tiled into more than 2400 images. It comprises over 83 000 unique human bounding box annotations for tropical tree crowns in dense canopies.
 
+SelvaBox is used to train and benchmark models in [CanopyRS](https://github.com/hugobaudchon/CanopyRS), a pipeline for detecting and segmenting tree crowns in high-resolution orthomosaics ([documentation](https://hugobaudchon.github.io/CanopyRS/)).
+
 ## Dataset Details
 
 ### Dataset Description
@@ -120,8 +122,8 @@ The 'Geographic Area % of total dataset column' more accurately describes how mu
 
 <!-- Provide the basic links for the dataset. -->
 
-- **Repository:** Will be added after double-blind review.
-- **Paper:** Will be added after double-blind review.
+- **Repository:** [CanopyRS](https://github.com/hugobaudchon/CanopyRS)
+- **Paper:** [SelvaBox — ICLR 2026](https://openreview.net/forum?id=GH7z1RURL6) · [arXiv:2507.00170](https://arxiv.org/abs/2507.00170)
 
 ## Uses
 
@@ -226,12 +228,6 @@ The annotations have been created by five domain experts with exact same instruc
 All annotators and reviewers were provided with documentation with difficult use cases as a reference when they were uncertain on the annotation procedure.
  As a comparison, one may note that annotations in OAM-TCD (NeurIPS 2024) were created by professional annotators that were not domain experts, and a part of these annotations were then reviewed by ecology experts.
 
-#### Who are the annotators?
-
-<!-- This section describes the people or systems who created the annotations. -->
-
-Will be added after double-blind review.
-
 <!-- #### Personal and Sensitive Information
 
 <!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. -->
@@ -250,8 +246,17 @@ Will be added after double-blind review.
 
 **BibTeX:**
 
-Will be added after double-blind review.
+```bibtex
+@inproceedings{
+baudchon2026selvabox,
+title={SelvaBox: A high\nobreakdash-resolution dataset for tropical tree crown detection},
+author={Hugo Baudchon and Arthur Ouaknine and Martin Weiss and M{\'e}lisande Teng and Thomas R. Walla and Antoine Caron-Guay and Christopher Pal and Etienne Lalibert{\'e}},
+booktitle={The Fourteenth International Conference on Learning Representations},
+year={2026},
+url={https://openreview.net/forum?id=GH7z1RURL6}
+}
+```
 
 ## Dataset Card Contact
 
-Will be added after double-blind review.
+hugo.baudchon@umontreal.ca