Update README.md

README.md

@@ -4,8 +4,6 @@ pretty_name: UAVLight
 task_categories:
 - image-to-image
 - image-to-3d
-- depth-estimation
-- robotics
 tags:
 - computer-vision
 - novel-view-synthesis
@@ -16,25 +14,22 @@ tags:
 - illumination-robustness
 - uav
 - outdoor-scenes
+- benchmark
 size_categories:
 - 1K<n<10K
 ---
 
 # UAVLight: A Benchmark for Illumination-Robust 3D Reconstruction in UAV Scenes
 
-<!-- 
-Teaser placeholder:
-Upload a teaser image to this repository, for example:
-assets/teaser.png
+![UAVLight teaser](assets/UAVLight_teaser.png)
 
-Then uncomment the line below:
+**UAVLight** is a benchmark dataset for evaluating **illumination-robust 3D reconstruction** and **novel-view synthesis** in outdoor UAV scenes. Unlike standard reconstruction datasets that are typically captured under relatively stable lighting, UAVLight focuses on challenging real-world scenarios where scene appearance changes significantly due to sunlight direction, cast shadows, exposure variation, and outdoor illumination conditions.
 
-![UAVLight teaser](assets/teaser.png)
--->
+The dataset provides multi-view UAV images, camera reconstruction files, predefined train/test splits, sun direction annotations, and optional geometry assets. It is designed to support research on lighting-aware reconstruction, robust novel-view synthesis, relighting-aware evaluation, and outdoor Gaussian Splatting / NeRF-style scene modeling.
 
-**UAVLight** is a benchmark dataset for evaluating **illumination-robust 3D reconstruction** and **novel-view synthesis** in outdoor UAV scenes. Unlike standard reconstruction datasets that are typically captured under relatively stable lighting, UAVLight focuses on challenging real-world scenarios where appearance can change significantly due to sunlight direction, shadows, exposure variation, and outdoor illumination conditions.
+A short video preview is also available:
 
-The dataset provides multi-view UAV images, camera reconstruction files, train/test splits, sun direction annotations, and optional geometry assets. It is designed to support research on lighting-aware reconstruction, robust novel-view synthesis, relighting-aware evaluation, and outdoor Gaussian Splatting / NeRF-style scene modeling.
+[Watch UAVLight video preview](assets/uavlight.mp4)
 
 This dataset accompanies the paper:
 
@@ -42,7 +37,9 @@ This dataset accompanies the paper:
 
 ## Overview
 
-UAVLight is intended to evaluate whether a 3D reconstruction or novel-view synthesis method can maintain stable geometry and appearance quality under outdoor illumination variations. The benchmark is particularly useful for studying:
+UAVLight is intended to evaluate whether a 3D reconstruction or novel-view synthesis method can maintain stable geometry and appearance quality under outdoor illumination variations. In UAV capture, the same scene may exhibit substantial appearance changes across different capture times, sun positions, shadow layouts, and camera trajectories. These changes can make reconstruction and view synthesis more difficult than in standard static-lighting benchmarks.
+
+The benchmark is particularly useful for studying:
 
 - illumination-robust 3D reconstruction
 - novel-view synthesis for UAV-captured scenes
@@ -61,6 +58,10 @@ The Hugging Face repository is organized as follows:
 UAVLight/
   README.md
 
+  assets/
+    UAVLight_teaser.png
+    uavlight.mp4
+
   data/
     <scene_id>.zip
     <scene_id>.zip
@@ -74,7 +75,7 @@ UAVLight/
     summary.txt
 ```
 
-The `data/` directory contains scene-level zip archives. Each zip file corresponds to one UAV scene. The `metadata/` directory provides summary files describing the released scenes, archive sizes, and file lists.
+The `data/` directory contains scene-level zip archives. Each zip file corresponds to one UAV scene. The `metadata/` directory provides summary files describing the released scenes, archive sizes, and file lists. The `assets/` directory contains visual materials used by this dataset card.
 
 ## Scene Archive Structure
 
@@ -112,7 +113,7 @@ For example:
 
 ### `images/`
 
-This folder contains the multi-view RGB images for the scene. These images are used as the main visual observations for reconstruction, novel-view synthesis, and evaluation.
+This folder contains the multi-view RGB images for the scene. These images are the main visual observations used for reconstruction, novel-view synthesis, and benchmark evaluation.
 
 ### `sparse/`
 
@@ -120,7 +121,7 @@ This folder contains sparse reconstruction files, such as camera poses and COLMA
 
 ### `split.csv`
 
-This file records the predefined data split information for the scene. It can be used to identify which images belong to training and testing subsets.
+This file records the predefined split information for the scene. It can be used to identify which images belong to training and testing subsets.
 
 ### `train_list.txt`
 
@@ -136,7 +137,7 @@ This file provides sun direction annotations associated with the scene/images. T
 
 ### `dense_points.ply`
 
-Dense point cloud reconstructed for the scene. This is provided as an optional geometry asset and may be useful for visualization, geometry analysis, or method initialization.
+A dense point cloud reconstructed for the scene. This is provided as an optional geometry asset and may be useful for visualization, geometry analysis, or method initialization.
 
 ### `downsampled_points.ply`
 
@@ -238,4 +239,4 @@ If you use UAVLight in your research, please cite:
 For questions about the dataset, please contact:
 
 **Kang Du**  
-Email: kdu800@connect.hkust-gz.edu.cn
+Email: kdu800@connect.hkust-gz.edu.cn