The Hazsense dataset is a multimodal collection of RGB-D data for detecting real-world hazards, as described in a 2025 IEEE conference paper. It was created by Shruti Brahma and Khaled Sayed and uploaded to Hugging Face by ShrutiBrahma. The dataset was last updated on April 6, 2026.
Use Cases
- Train hazard detection models based on the multimodal RGB-D data mentioned in the description.
- Benchmark computer vision algorithms for safety applications using real-world hazard scenes.
- Develop multimodal fusion techniques for RGB and depth data in safety-critical environments.
Strengths
- Dataset is associated with a peer-reviewed IEEE conference paper from 2025.
- Last updated on April 6, 2026, suggesting recent maintenance.
Limitations
- Description metadata is limited; actual data quality requires manual inspection after download.
- Column-level documentation is absent; field semantics must be inferred after download.
- Row count is unknown, which may limit suitability assessment.
Provenance
- Source
- Shruti Brahma and Khaled Sayed, authors of the associated IEEE paper.
- Collection Method
- Likely collected for research on hazard detection, as per the paper title.
- Freshness
- Last updated 2026-04-06 18:41:20