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RawSLAM: Online HDR Gaussian SLAM from Linear Radiance
Current dense visual SLAM systems rely almost exclusively on 8-bit tonemapped Low Dynamic Range (LDR) inputs, limiting their robustness in extreme lighting where shadows and highlights trigger tracking drift and mapping collapse. Conversely, existing raw and High Dynamic Range (HDR) reconstruction pipelines operate strictly offline. They depend on Structure-from-Motion preprocessing and are not suited for large inter-frame motion. We present, to the best of our knowledge, the first online Gaussian SLAM framework that tracks and maps directly on single-exposure 16-bit linear HDR imagery. Our me
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-17T15:41:32.000Z
First collected: 2026-09-19T20:28:14.107Z. This is not the publication date.