Honda Scenes Dataset


The Honda Scenes dataset is a large scale annotated dataset created to enable dynamic scene classification. The dataset contains 80 hours of diverse high quality driving video data clips collected in the San Francisco Bay area. The dataset includes temporal annotations for road places, road environment, weather, and road surface conditions. HSD has the following specifications:

  • The dataset contains 11 classes of road places - 3-way intersection, 4-way intersection, 5-way intersection, overhead bridge, railway crossing, construction zone, merge with gore on left, merge with gore on right, branch with gore on left, branch with gore on right, zebra crossing.
  • The dataset spans 4 classes of road environments - rural, urban, highway and ramp and 4 weather conditions - rainy, sunny, cloudy, and foggy.
  • Most classes have 3 temporal sub-classes , including approaching, entering, and passing.    The merge and branch classes have approaching and passing sub-classes, while the zebra-crossing class has just approaching.
  • The dataset contains a total of about 20,000 instances spanned over these 11 classes.

The figures below outline key statistics in the dataset.




3-Way-Intersection 3

3-Way-Intersection 2

3-Way-Intersection 1

4-Way-Intersection 2

4-Way-Intersection 3

5-Way-Intersection 1

5-Way-Intersection 2

Branch Gore On Left 1

Branch Gore On Left 2

Branch Gore On Left 3

Branch Gore On Right 1

Branch Gore On Right 2

Branch Gore On Right 3

Construction Zone 1

Construction Zone 2

Construction Zone 3

Merge Gore On Left 1

Merge Gore On Left 2

Merge Gore On Left 3

Merge Gore On Right 1

Merge Gore On Right 2

Merge Gore On Right 3

Overhead Bridge 1

Overhead Bridge 2

Overhead Bridge 3

Railway 1

Railway 2

Railway 3

Tunnel 1

Tunnel 2

Tunnel 3

Zebra Crossing 1

Zebra Crossing 2

Zebra Crossing 3


This dataset corresponds to the paper, "Dynamic Traffic Scene Classification with Space-Time Coherence", as it appears in the proceedings of International Conference on Robotics and Automation (ICRA) 2019. In the current release, the dataset is only being made available to researchers in universities in the United States. The process to obtain the dataset is as follows:

  • If you are affiliated with a university in the United States, please send email tousing your official university email account.   

  • A "Data Sharing Agreement"  will be sent to you and must be signed by a university representative (typically a university professor, not a student).

  • After execution of this agreement, a link and password to download the dataset will be provided.


Please cite the following paper if you find the dataset useful in your work:

    author = {Athma Narayanan and Isht Dwivedi and Behzad Dariush},
    title = {Dynamic Traffic Scene Classification with Space-Time Coherence},
    booktitle = {International Conference on Robotics and Automation},
    year = {2019}