This paper releases and benchmarks a 30 km egocentric day-and-night dataset with SLAM poses and TLS ground truth, and shows current NVS and relocalization methods degrade sharply at night.
Matterport3D: Learning from RGB-D data in indoor environments
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Seeing in the Dark: Benchmarking Egocentric 3D Vision with the Oxford Day-and-Night Dataset
This paper releases and benchmarks a 30 km egocentric day-and-night dataset with SLAM poses and TLS ground truth, and shows current NVS and relocalization methods degrade sharply at night.