The M2I dataset is a synthetic dataset introduced in the paper 'MIC-BEV: Multi-Infrastructure Camera Bird's-Eye-View Transformer with Relation-Aware Fusion for 3D Object Detection'. It is designed to support training and evaluation of models for infrastructure-based multi-camera 3D object detection. The dataset was uploaded by author 'handsomeYun' and last updated on December 13, 2025.
Use Cases
- Training multi-camera 3D object detection models based on the dataset's diverse camera configurations.
- Evaluating model robustness across different road layouts and environmental conditions as described.
- Developing bird's-eye-view fusion algorithms for infrastructure-based perception systems.
Strengths
- Designed for a specific, advanced research task: infrastructure-based multi-camera 3D object detection.
- Features diverse camera configurations, road layouts, and environmental conditions as noted in the description.
Limitations
- Column-level documentation is absent; field semantics must be inferred after download.
- Row count is unknown, which may limit suitability assessment.
- The dataset is synthetic, which may limit real-world applicability.
Provenance
- Source
- huggingface
- Collection Method
- Synthetic generation, as described.
- Time Range
- null
- Freshness
- Last updated 2025-12-13 00:11:14; freshness should be verified.
- Geography
- null