Depth-guided Multi-view Exposure Bracketing for HDR Robot Vision

Achieving reliable single-shot high dynamic range (HDR)imaging under extreme illumination conditions remains a long-standingchallenge, yet no comprehensive benchmark exist for evaluating HDRperception in multi-sensor robotic systems. To fill this gap, we intro-duce a large-scale dataset collected via a custom robotic vision platformand an iPhone 13 Pro: 121 real-world scenes spanning modest and ultra-high dynamic range conditions, alongside 20 synthetic video sequencesfrom the CARLA simulator. As a reference pipeline for this dataset,we propose Depth-guided Multi-view Exposure Bracketing (DMEB), asingle-shot HDR method that distributes drastically different exposuresacross multi-view low-bit-depth cameras and fuses them via depth-guidedconfidence-aware fusion. Evaluations on our dataset show that DMEBestablishes a strong reference point and highlight the promise of thissensor configuration for robust HDR perception in diverse multi-cameraand depth sensor system.