Cross-spectral Gated-RGB Stereo Depth Estimation
<|reference_start|>Cross-spectral Gated-RGB Stereo Depth Estimation: Gated cameras flood-illuminate a scene and capture the time-gated impulse response of a scene. By employing nanosecond-scale gates, existing sensors are capable of capturing mega-pixel gated images, delivering dense depth improving on today's LiDAR sensors in spatial resolution and depth precision. Although gated depth estimation methods deliver a million of depth estimates per frame, their resolution is still an order below existing RGB imaging methods. In this work, we combine high-resolution stereo HDR RCCB cameras with gated imaging, allowing us to exploit depth cues from active gating, multi-view RGB and multi-view NIR sensing -- multi-view and gated cues across the entire spectrum. The resulting capture system consists only of low-cost CMOS sensors and flood-illumination. We propose a novel stereo-depth estimation method that is capable of exploiting these multi-modal multi-view depth cues, including the active illumination that is measured by the RCCB camera when removing the IR-cut filter. The proposed method achieves accurate depth at long ranges, outperforming the next best existing method by 39% for ranges of 100 to 220m in MAE on accumulated LiDAR ground-truth. Our code, models and datasets are available at https://light.princeton.edu/gatedrccbstereo/ .<|reference_end|>
@article{brucker2024cross-spectral,
    title={Cross-spectral Gated-RGB Stereo Depth Estimation},
    author={Samuel Brucker, Stefanie Walz, Mario Bijelic, Felix Heide},
    journal={arXiv preprint arXiv:2405.12759},
    year={2024},
    archivePrefix={arXiv},
    eprint={2405.12759},
    primaryClass={cs.CV}
}