revise source linkage

README.md

@@ -27,7 +27,7 @@ size_categories:
 description: "Cropped images of zebras from KABR drone footage labeled with one of eight pose orientations (front, front-left, left, back-left, back, back-right, right, front-right). Intended as training data for a pose / viewpoint classifier used in autonomous drone navigation around wildlife."
 ---
 
-# Dataset Card for KABR-poses
+# Dataset Card for KABR-poses: Pose Orientation Labels for Zebras in KABR Drone Footage
 
 Cropped zebra images from KABR drone footage, manually labeled with one of eight discrete pose orientations relative to the camera. The dataset was curated to train a pose / viewpoint classifier (DINOv2 backbone + MLP head) for the [WildWing](https://github.com/Imageomics/wildwing) autonomous drone-navigation system, where knowing which side of an animal is visible drives both individual re-identification (matching against flank stripe patterns) and behavior-aware flight decisions (e.g., avoiding approaches from the front).
 
@@ -39,16 +39,16 @@ Cropped zebra images from KABR drone footage, manually labeled with one of eight
 
 ### Dataset Description
 
-- **Curated by:** Claire (curator), with the [Imageomics Institute](https://imageomics.org) and [WildWing](https://imageomics.github.io/wildwing/) project teams
+- **Curated by:** Claire Sun (curator), with the [Imageomics Institute](https://imageomics.org) and [WildWing](https://imageomics.github.io/wildwing/) project teams
 - **Language(s) (NLP):** en
-- **Homepage:** https://huggingface.co/datasets/imageomics/KABR-poses
-- **Repository:** https://github.com/Imageomics/wildwing
-- **Related dataset:** [imageomics/KABR](https://huggingface.co/datasets/imageomics/KABR) (source drone footage)
+- **Homepage:** [KABR](https://imageomics.github.io/KABR/) and [WildWing](https://imageomics.github.io/wildwing/)
+- **Repository:** [WildWing Repo](https://github.com/Imageomics/wildwing)
+- **Related datasets:** [imageomics/KABR](https://huggingface.co/datasets/imageomics/KABR); [KABR raw videos](https://huggingface.co/datasets/imageomics/KABR-raw-videos) and [KABR mini-scene raw videos](https://huggingface.co/datasets/imageomics/KABR-mini-scene-raw-videos) (source drone footage)
 - **Paper:** N/A (dataset release)
 
-This dataset contains 988 manually labeled 224x224 RGB crops of zebras observed in aerial drone footage from the Mpala Research Centre, Kenya. Each crop is assigned exactly one of eight pose-orientation labels describing which flank of the zebra is visible to the camera (equivalently, the direction of the zebra's head relative to the camera). An additional 35 ambiguous or unusable crops are preserved in a `_skip/` folder to document labeling decisions.
+This dataset contains 988 manually labeled 224x224 RGB crops of zebras observed in aerial drone footage from the [Mpala Research Centre](https://mpala.org/), Kenya. Each crop is assigned exactly one of eight pose-orientation labels describing which flank of the zebra is visible to the camera (equivalently, the direction of the zebra's head relative to the camera). An additional 35 ambiguous or unusable crops are preserved in a `_skip/` folder to document labeling decisions.
 
-The labels were created to train the pose component of the WildWing drone-navigation stack. WildWing combines a YOLO-based animal detector with a pose classifier so the drone can reason about how each animal in its view is oriented and make better autonomous decisions about positioning. Reliable pose estimates are particularly important for individual re-identification of zebras, which depends on matching the lateral stripe pattern \- so the classifier needs to know when a useful side view (left or right profile) is available versus when the animal is facing toward or away from the camera.
+The labels were created to train the pose component of the [WildWing drone-navigation stack](https://imageomics.github.io/wildwing/). WildWing combines a YOLO-based animal detector with a pose classifier so the drone can reason about how each animal in its view is oriented and make better autonomous decisions about positioning. Reliable pose estimates are particularly important for individual re-identification of zebras, which depends on matching the lateral stripe pattern \- so the classifier needs to know when a useful side view (left or right profile) is available versus when the animal is facing toward or away from the camera.
 
 ### Supported Tasks and Leaderboards
 
@@ -131,7 +131,7 @@ The 8-class scheme is therefore designed to be both coarse enough to label relia
 
 #### Data Collection and Processing
 
-Source frames were drawn from the same drone footage used in the [KABR dataset](https://huggingface.co/datasets/imageomics/KABR), collected at the Mpala Research Centre in Kenya in January 2023. Animals were detected in each frame with a YOLO v11 detector trained for aerial wildlife imagery (see [imageomics/mmla](https://huggingface.co/imageomics/mmla)), each bounding box was cropped from the source frame, and the resulting crops were resized to 224x224 for compatibility with the DINOv2 backbone used in the downstream classifier. Crops were sampled across multiple Mpala sessions and source videos to cover varying lighting conditions, terrain, herd densities, and altitudes.
+Source frames were drawn from the same drone footage used in the [KABR dataset](https://huggingface.co/datasets/imageomics/KABR), collected at the Mpala Research Centre in Kenya in January 2023 ([mini-scene raw videos](https://huggingface.co/datasets/imageomics/KABR-mini-scene-raw-videos) and [raw videos not used in mini-scenes](https://huggingface.co/datasets/imageomics/KABR-raw-videos)). Animals were detected in each frame with a YOLO v11 detector trained for aerial wildlife imagery (see [imageomics/mmla](https://huggingface.co/imageomics/mmla)), each bounding box was cropped from the source frame, and the resulting crops were resized to 224x224 for compatibility with the DINOv2 backbone used in the downstream classifier. Crops were sampled across multiple Mpala sessions and source videos to cover varying lighting conditions, terrain, herd densities, and altitudes.
 
 #### Who are the source data producers?
 
@@ -183,15 +183,16 @@ This dataset is dedicated to the public domain under [CC0 1.0 Universal](https:/
 **Data**
 ```
 @misc{kabr-poses-2026,
-  author       = {Claire and Kline, Jenna},
+  author       = {Sun, Claire and Kline, Jenna},
   title        = {KABR-poses: Pose Orientation Labels for Zebras in KABR Drone Footage},
   year         = {2026},
   url          = {https://huggingface.co/datasets/imageomics/KABR-poses},
-  publisher    = {Hugging Face}
+  publisher    = {Hugging Face},
+  doi          = {<add once generated>}
 }
 ```
 
-Please also cite the underlying KABR dataset and paper:
+Please also cite the underlying KABR datasets ([raw videos](https://huggingface.co/datasets/imageomics/KABR-raw-videos) and [mini-scene raw videos](https://huggingface.co/datasets/imageomics/KABR-mini-scene-raw-videos)) and paper:
 
 **Underlying drone footage (KABR)**
 ```
@@ -222,7 +223,7 @@ For details on the downstream classifier architecture (DINOv2 + MLP head), train
 
 ## Dataset Card Authors
 
-Claire and Jenna Kline (Imageomics Institute / WildWing project).
+Claire Sun and Jenna Kline (Imageomics Institute / WildWing project).
 
 ## Dataset Card Contact