Bengaluru Semantic Occupancy Dataset

Dataset Summary

We gathered a dataset spanning 114 minutes and 165K frames in Bengaluru, India. Our dataset consists of video data from a calibrated camera sensor with a resolution of 1920×1080 recorded at a framerate of 30 Hz. We utilize a Depth Dataset Generation pipeline that only uses videos as input to produce high-resolution disparity maps.

Dataset Iterator: https://github.com/AdityaNG/bdd_dataset_iterator
Project Page: https://adityang.github.io/AdityaNG/BengaluruDrivingDataset/
Dataset Download: https://huggingface.co/datasets/AdityaNG/BengaluruSemanticOccupancyDataset

Paper

Bengaluru Driving Dataset: 3D Occupancy Convolutional Transformer Network in Unstructured Traffic Scenarios

Citation

```bibtex @misc{analgund2023octran, title={Bengaluru Driving Dataset: 3D Occupancy Convolutional Transformer Network in Unstructured Traffic Scenarios}, author={Ganesh, Aditya N and Pobbathi Badrinath, Dhruval and Kumar, Harshith Mohan and S, Priya and Narayan, Surabhi }, year={2023}, howpublished={Spotlight Presentation at the Transformers for Vision Workshop, CVPR}, url={https://sites.google.com/view/t4v-cvpr23/papers#h.enx3bt45p649}, note={Transformers for Vision Workshop, CVPR 2023} }