New #ECCV2026 paper alert: 🧭 AutoCompass: Accurate Visual Localization on Public Maps by Learning from Weak Labels 🧭 Paper: arxiv.org/abs/2609.02798 Website: nianticspatial.github.io/autocompass/ Video: www.youtube.com/watch?v=hmUF...
- AutoCompass trains neural map matchers using only raw GPS labels and shows heading labels are unnecessary because models learn heading automatically.
- The method adds a tolerance region around each noisy GPS point and, when available, uses relative poses from SLAM or SfM as a stronger signal.
- The authors report gains over absolute-pose-supervised baselines on both driving and egocentric localization benchmarks.