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CLEAR-IR: Reconstructing Infrared Images into RGB-Style Images to Support Robot Perception in Dark Environments

CLEAR-IR proposes a dual-stream architecture that reconstructs clean, RGB-style images from infrared images containing structured-light emitter patterns, allowing vision pipelines originally trained on RGB to keep working when no visible light is available. Inspired by DeepMAO, the architecture was evaluated on object detection, ArUco marker detection, and visual SLAM, covering scenarios ranging from well-lit to completely dark; in complete darkness, passive RGB enhancement methods fail because the sensor receives no signal. The paper has been accepted to IEEE/RSJ IROS 2026.

Part of the event: CLEAR-IR Infrared Image Reconstruction Framework Released

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