AsymLoc uses teacher-student distillation with geometry-driven matching to enable efficient nearest-neighbor feature matching, achieving 95% of teacher accuracy with 10x smaller models on localization benchmarks.
City-scale localization for cameras with known ver- tical direction.IEEE PAMI, 39(7):1455–1461
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AsymLoc: Towards Asymmetric Feature Matching for Efficient Visual Localization
AsymLoc uses teacher-student distillation with geometry-driven matching to enable efficient nearest-neighbor feature matching, achieving 95% of teacher accuracy with 10x smaller models on localization benchmarks.