Datasets:

hoffman-lab
/

SkyScenes

Tasks:

Object Detection

Depth Estimation

Image Segmentation

Languages:

ArXiv:

Tags:

domain adaptation

License:

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apal commited on Sep 25

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@@ -24,7 +24,6 @@ tags:
 [![HuggingFace Dataset](https://img.shields.io/badge/🤗-HuggingFace%20Dataset-cyan.svg)](https://huggingface.co/datasets/hoffman-lab/SkyScenes)[![Project Page](https://img.shields.io/badge/Project-Website-orange)](https://hoffman-group.github.io/SkyScenes/)[![arXiv](https://img.shields.io/badge/arXiv-SkyScenes-b31b1b.svg)](https://arxiv.org/abs/2312.06719)
 <img src="./assets/teaser.jpeg" width="100%"/>
 ## Dataset Summary
 Real-world aerial scene understanding is limited by a lack of datasets that contain densely annotated images curated under a diverse set of conditions.
@@ -33,6 +32,9 @@ we present SkyScenes, a synthetic dataset of densely annotated aerial images cap
 **SkyScenes** images are carefully curated from **CARLA** to comprehensively capture diversity across layout (urban and rural maps), weather conditions, times of day, pitch angles and altitudes with corresponding semantic, instance and depth annotations.
 **SkyScenes** features **33,600** images in total, which are spread across 8 towns, 5 weather and daytime conditions and 12 height and pitch variations.
 <details>
   <summary>Click to view the detailed list of all variations</summary>

 [![HuggingFace Dataset](https://img.shields.io/badge/🤗-HuggingFace%20Dataset-cyan.svg)](https://huggingface.co/datasets/hoffman-lab/SkyScenes)[![Project Page](https://img.shields.io/badge/Project-Website-orange)](https://hoffman-group.github.io/SkyScenes/)[![arXiv](https://img.shields.io/badge/arXiv-SkyScenes-b31b1b.svg)](https://arxiv.org/abs/2312.06719)
 <img src="./assets/teaser.jpeg" width="100%"/>
 ## Dataset Summary
 Real-world aerial scene understanding is limited by a lack of datasets that contain densely annotated images curated under a diverse set of conditions.
 **SkyScenes** images are carefully curated from **CARLA** to comprehensively capture diversity across layout (urban and rural maps), weather conditions, times of day, pitch angles and altitudes with corresponding semantic, instance and depth annotations.
 **SkyScenes** features **33,600** images in total, which are spread across 8 towns, 5 weather and daytime conditions and 12 height and pitch variations.
+## 📣 Announcement
+SkyScenes has been accepted at [ECCV 2024](https://www.ecva.net/papers/eccv_2024/papers_ECCV/html/10113_ECCV_2024_paper.php)
 <details>
   <summary>Click to view the detailed list of all variations</summary>