Semantic Match Consistency for Long-Term Visual Localization

ECCV 2018 Carl ToftErik StenborgLars HammarstrandLucas BrynteMarc PollefeysTorsten SattlerFredrik Kahl

Robust and accurate visual localization across large appearance variations due to changes in time of day, seasons, or changes of the environment is a challenging problem which is of importance to application areas such as navigation of autonomous robots. Traditional feature-based methods often struggle in these conditions due to the significant number of erroneous matches between the image and the 3D model... (read more)

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