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We propose Gated Stereo, a high-resolution and long-range depth estimationtechnique that operates on active gated stereo images. Using active and highdynamic range passive captures, Gated Stereo exploits multi-view cues alongsidetime-of-flight intensity cues from active gating. To this end, we propose adepth estimation method with a monocular and stereo depth prediction branchwhich are combined in a final fusion stage. Each block is supervised through acombination of supervised and gated self-supervision losses. To facilitatetraining and validation, we acquire a long-range synchronized gated stereodataset for automotive scenarios. We find that the method achieves animprovement of more than 50 % MAE compared to the next best RGB stereo method,and 74 % MAE to existing monocular gated methods for distances up to 160 m. Ourcode,models and datasets are available here.

Gated Stereo: Joint Depth Estimation from Gated and Wide-Baseline Active Stereo Cues