MUSES: MUlti-SEnsor Semantic perception dataset

MUSES offers 2500 multi-modal scenes, evenly distributed across various combinations of weather conditions (clear, fog, rain, and snow) and types of illumination (daytime, nighttime). Each image includes high-quality 2D pixel-level panoptic annotations and class-level and novel instance-level uncertainty annotations. Further, each adverse-condition image has a corresponding image of the same scene taken under clear-weather, daytime conditions. The annotation process for MUSES utilizes all available sensor data, allowing the annotators to also reliably label degraded image regions that are still discernible in other modalities. This results in better pixel coverage in the annotations and creates a more challenging evaluation setup.

The dataset provides public benchmarks for:

• Panoptic segmentation
• Uncertainty-aware panoptic segmentation
• Semantic segmentation
• Object detection

Sensor modalities included:

• Frame camera (RGB)
• MEMS lidar
• FMCW radar
• HD event camera
• IMU/GNSS sensor