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--- |
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license: mit |
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language: |
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- en |
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--- |
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<div align="center"> |
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# SkyScenes: A Synthetic Dataset for Aerial Scene Understanding |
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[Sahil Khose](https://sahilkhose.github.io/)\*, [Anisha Pal](https://anipal.github.io/)\*, [Aayushi Agarwal](https://www.linkedin.com/in/aayushiag/)\*, [Deepanshi Deepanshi](https://www.linkedin.com/in/deepanshi-d/)\*, [Judy Hoffman](https://faculty.cc.gatech.edu/~judy/), [Prithvijit Chattopadhyay](https://prithv1.xyz/) |
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</div> |
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<!-- This repository is the official Pytorch implementation for [SkyScenes](). --> |
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[](https://huggingface.co/datasets/hoffman-lab/SkyScenes) []() []() |
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<!-- [](./assets/robust_aerial_videos.mp4) --> |
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<img src="./assets/skyscene_intro_teaser.png" width="100%"/> |
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## Dataset Summary |
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Real-world aerial scene understanding is limited by a lack of datasets that contain densely annotated images curated under a diverse set of conditions. |
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Due to inherent challenges in obtaining such images in controlled real-world settings, |
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we present SkyScenes, a synthetic dataset of densely annotated aerial images captured from Unmanned Aerial Vehicle (UAV) perspectives. |
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**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. |
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**SkyScenes** features **33,600** images in total, which are spread across 8 towns, 5 weather and daytime conditions and 12 height and pitch variations. |
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<details> |
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<summary>Click to view the detailed list of all variations</summary> |
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- **Layout Variations(Total 8):**: |
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- Town01 |
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- Town02 |
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- Town03 |
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- Town04 |
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- Town05 |
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- Town06 |
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- Town07 |
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- Town10HD |
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_Town07 features Rural Scenes, whereas the rest of the towns feature Urban scenes_ |
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- **Weather & Daytime Variations(Total 5):** |
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- ClearNoon |
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- ClearSunset |
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- ClearNight |
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- CloudyNoon |
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- MidRainyNoon |
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- **Height and Pitch Variations of UAV Flight(Total 12):** |
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- Height = 15m, Pitch = 0° |
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- Height = 15m, Pitch = 45° |
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- Height = 15m, Pitch = 60° |
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- Height = 15m, Pitch = 90° |
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- Height = 35m, Pitch = 0° |
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- Height = 35m, Pitch = 45° |
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- Height = 35m, Pitch = 60° |
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- Height = 35m, Pitch = 90° |
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- Height = 60m, Pitch = 0° |
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- Height = 60m, Pitch = 45° |
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- Height = 60m, Pitch = 60° |
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- Height = 60m, Pitch = 90° |
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</details> |
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<details> |
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<summary>Click to view class definitions, color palette and class IDs for Semantic Segmentation</summary> |
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**SkyScenes** semantic segmentation labels span 28 classes which can be further collapsed to 20 classes. |
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| Class ID | Class ID (collapsed) | RGB Color Palette | Class Name | Definition | |
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|----------|--------------------|-------------------|------------------|----------------------------------------------------------------------------------------------------| |
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| 0 | -1 | <span style="color:rgb(0, 0, 0)"> (0, 0, 0) </span> | unlabeled | Elements/objects in the scene that have not been categorized | |
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| 1 | 2 | <span style="color:rgb(70, 70, 70)"> (70, 70, 70) </span> | building | Includes houses, skyscrapers, and the elements attached to them | |
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| 2 | 4 | <span style="color:rgb(190, 153, 153)"> (190, 153, 153) </span> | fence | Wood or wire assemblies that enclose an area of ground | |
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| 3 | -1 | <span style="color:rgb(55, 90, 80)"> (55, 90, 80) </span> | other | Uncategorized elements | |
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| 4 | 11 | <span style="color:rgb(220, 20, 60)"> (220, 20, 60) </span> | pedestrian | Humans that walk | |
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| 5 | 5 | <span style="color:rgb(153, 153, 153)"> (153, 153, 153) </span> | pole | Vertically oriented pole and its horizontal components if any | |
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| 6 | 16 | <span style="color:rgb(157, 234, 50)"> (157, 234, 50) </span> | roadline | Markings on road | |
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| 7 | 0 | <span style="color:rgb(128, 64, 128)"> (128, 64, 128) </span> | road | Lanes, streets, paved areas on which cars drive | |
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| 8 | 1 | <span style="color:rgb(244, 35, 232)"> (244, 35, 232) </span> | sidewalk | Parts of ground designated for pedestrians or cyclists | |
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| 9 | 8 | <span style="color:rgb(107, 142, 35)"> (107, 142, 35) </span> | vegetation | Trees, hedges, all kinds of vertical vegetation (ground-level vegetation is not included here) | |
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| 10 | 13 | <span style="color:rgb(0, 0, 142)"> (0, 0, 142) </span> | cars | Cars in scene | |
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| 11 | 3 | <span style="color:rgb(102, 102, 156)"> (102, 102, 156) </span> | wall | Individual standing walls, not part of buildings | |
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| 12 | 7 | <span style="color:rgb(220, 220, 0)"> (220, 220, 0) </span> | traffic sign | Signs installed by the state/city authority, usually for traffic regulation | |
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| 13 | 10 | <span style="color:rgb(70, 130, 180)"> (70, 130, 180) </span> | sky | Open sky, including clouds and sun | |
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| 14 | -1 | <span style="color:rgb(81, 0, 81)"> (81, 0, 81) </span> | ground | Any horizontal ground-level structures that do not match any other category | |
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| 15 | -1 | <span style="color:rgb(150, 100, 100)"> (150, 100, 100) </span> | bridge | The structure of the bridge | |
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| 16 | -1 | <span style="color:rgb(230, 150, 140)"> (230, 150, 140) </span> | railtrack | Rail tracks that are non-drivable by cars | |
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| 17 | -1 | <span style="color:rgb(180, 165, 180)"> (180, 165, 180) </span> | guardrail | Guard rails / crash barriers | |
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| 18 | 6 | <span style="color:rgb(250, 170, 30)"> (250, 170, 30) </span> | traffic light | Traffic light boxes without their poles | |
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| 19 | -1 | <span style="color:rgb(110, 190, 160)"> (110, 190, 160) </span> | static | Elements in the scene and props that are immovable | |
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| 20 | -1 | <span style="color:rgb(170, 120, 50)"> (170, 120, 50) </span> | dynamic | Elements whose position is susceptible to change over time | |
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| 21 | 19 | <span style="color:rgb(45, 60, 150)"> (45, 60, 150) </span> | water | Horizontal water surfaces | |
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| 22 | 9 | <span style="color:rgb(152, 251, 152)"> (152, 251, 152) </span> | terrain | Grass, ground-level vegetation, soil, or sand | |
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| 23 | 12 | <span style="color:rgb(255, 0, 0)"> (255, 0, 0) </span> | rider | Humans that ride/drive any kind of vehicle or mobility system | |
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| 24 | 18 | <span style="color:rgb(119, 11, 32)"> (119, 11, 32) </span> | bicycle | Bicycles in scenes | |
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| 25 | 17 | <span style="color:rgb(0, 0, 230)"> (0, 0, 230) </span> | motorcycle | Motorcycles in scene | |
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| 26 | 15 | <span style="color:rgb(0, 60, 100)"> (0, 60, 100) </span> | bus | Buses in scenes | |
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| 27 | 14 | <span style="color:rgb(0, 0, 70)"> (0, 0, 70) </span> | truck | Trucks in scenes | |
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</details> |
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## Dataset Structure |
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The dataset is organized in the following structure: |
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<!--<details> |
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<summary><strong>Images (RGB Images)</strong></summary> |
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- ***H_15_P_0*** |
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- *ClearNoon* |
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- Town01.tar.gz |
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- Town02.tar.gz |
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- ... |
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- Town10HD.tar.gz |
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- *ClearSunset* |
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- Town01.tar.gz |
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- Town02.tar.gz |
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- ... |
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- Town10HD.tar.gz |
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- *ClearNight* |
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- Town01.tar.gz |
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- Town02.tar.gz |
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- ... |
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- Town10HD.tar.gz |
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- *CloudyNoon* |
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- Town01.tar.gz |
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- Town02.tar.gz |
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- ... |
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- Town10HD.tar.gz |
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- *MidRainyNoon* |
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- Town01.tar.gz |
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- Town02.tar.gz |
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- ... |
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- Town10HD.tar.gz |
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- ***H_15_P_45*** |
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- ... |
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- ... |
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- ***H_60_P_90*** |
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- ... |
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</details> |
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<details> |
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<summary><strong>Instance (Instance Segmentation Annotations)</strong></summary> |
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- ***H_35_P_45*** |
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- *ClearNoon* |
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- Town01.tar.gz |
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- Town02.tar.gz |
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- ... |
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- Town10HD.tar.gz |
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</details> |
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<details> |
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<summary><strong>Segment (Semantic Segmentation Annotations)</strong></summary> |
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- ***H_15_P_0*** |
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- *ClearNoon* |
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- Town01.tar.gz |
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- Town02.tar.gz |
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- ... |
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- Town10HD.tar.gz |
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- ***H_15_P_45*** |
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- ... |
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- ... |
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- ***H_60_P_90*** |
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</details> |
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<details> |
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<summary><strong>Depth (Depth Annotations)</strong></summary> |
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- ***H_35_P_45*** |
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- *ClearNoon* |
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- Town01.tar.gz |
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- Town02.tar.gz |
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- ... |
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- Town10HD.tar.gz |
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</details> |
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--> |
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``` |
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├── Images (RGB Images) |
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├── H_15_P_0 |
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│ ├── ClearNoon |
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│ │ ├── Town01.tar.gz |
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│ │ ├── Town02.tar.gz |
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│ │ ├── ... |
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│ │ └── Town10HD.tar.gz |
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│ ├── ClearSunset |
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│ │ ├── Town01.tar.gz |
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│ │ ├── Town02.tar.gz |
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│ │ ├── ... |
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│ │ └── Town10HD.tar.gz |
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│ ├── ClearNight |
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│ │ ├── Town01.tar.gz |
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│ │ ├── Town02.tar.gz |
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│ │ ├── ... |
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│ │ └── Town10HD.tar.gz |
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│ ├── CloudyNoon |
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│ │ ├── Town01.tar.gz |
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│ │ ├── Town02.tar.gz |
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│ │ ├── ... |
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│ │ └── Town10HD.tar.gz |
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│ └── MidRainyNoon |
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│ ├── Town01.tar.gz |
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│ ├── Town02.tar.gz |
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│ ├── ... |
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│ └── Town10HD.tar.gz |
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├── H_15_P_45 |
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│ └── ... |
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├── ... |
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└── H_60_P_90 |
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└── ... |
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└── Instance (Instance Segmentation Annotations) |
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├── H_35_P_45 |
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│ └── ClearNoon |
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│ ├── Town01.tar.gz |
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│ ├── Town02.tar.gz |
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│ ├── ... |
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│ └── Town10HD.tar.gz |
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└── ... |
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└── Segment (Semantic Segmentation Annotations) |
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├── H_15_P_0 |
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│ ├── ClearNoon |
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│ │ ├── Town01.tar.gz |
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│ │ ├── Town02.tar.gz |
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│ │ ├── ... |
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│ │ └── Town10HD.tar.gz |
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│ ├── H_15_P_45 |
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│ │ └── ... |
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│ ├── ... |
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│ └── H_60_P_90 |
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│ └── ... |
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└── ... |
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└── Depth (Depth Annotations) |
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├── H_35_P_45 |
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│ └── ClearNoon |
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│ ├── Town01.tar.gz |
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│ ├── Town02.tar.gz |
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│ ├── ... |
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│ └── Town10HD.tar.gz |
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└── ... |
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``` |
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**Note**: Since the same viewpoint is reproduced across each weather variation, hence ClearNoon annotations can be used for all images pertaining to the different weather variations. |
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