SPIN-UV

SPIN-UV is a multimodal dataset for unstructured scene understanding in dense urban villages. It was collected from a motor-driven, human-steered single-track vehicle and pairs front-facing visual observations with frame-anchored riding-state signals. The dataset is intended to support semantic segmentation, RGB-D perception, state-conditioned traversability, temporal consistency, and motion-aware scene understanding in narrow, weakly structured urban-village corridors.

SPIN stands for Scene, Proprioception, Interaction, and Navigation. UV refers to the urban-village setting that anchors the dataset.

Dataset Components

The release contains two complementary parts.

`dataset_seg_split/`

This is the ready-to-train semantic-segmentation subset. It contains anonymized RGB images and COCO polygon annotations, split at sequence level into train, validation, and test partitions.

Each split folder contains PNG images and one COCO annotation file:

dataset_seg_split/
  train/
    *.png
    _annotations.coco.json
  val/
    *.png
    _annotations.coco.json
  test/
    *.png
    _annotations.coco.json

The split is sequence-level rather than image-level, so frames sampled from the same traversal do not cross train, validation, and test partitions.

`dataset_sequences/`

This is the processed raw multimodal sequence release. It contains 89 traversal sequences and 132,293 uploaded files after excluding per-sequence config_snapshot.json files.

Verified raw-sequence statistics: