KITTI-Hazy-optical-flow is a dataset derived from the KITTI autonomous driving benchmark. The dataset likely contains image sequences with corresponding optical flow fields, modified to include synthetic atmospheric haze. Its specific scale, creation date, and author are not detailed in the provided metadata.
Use Cases
- Training optical flow estimation models under simulated haze conditions (inferred from domain, verify after download)
- Benchmarking the robustness of autonomous driving perception systems to weather degradation (inferred from domain, verify after download)
- Developing image dehazing or enhancement algorithms using paired clear and hazy frames (inferred from domain, verify after download)
Strengths
- Published on Kaggle, a major platform for sharing datasets.
- Builds upon the established KITTI autonomous driving benchmark.
Limitations
- Metadata is minimal; actual content requires verification after download.
- Column-level documentation is absent; field semantics must be inferred after download.
- Row count, file formats, and license are unknown, which may limit suitability assessment.
Provenance
- Source
- KITTI benchmark
- Collection Method
- Likely a derived dataset with synthetic haze applied to original KITTI sequences.