{"paper":{"title":"Altitude-Adaptive Vision-Only Geo-Localization for UAVs in GPS-Denied Environments","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"Estimating relative altitude from one downward image normalizes scale and raises UAV retrieval recall by over 40 points.","cross_cats":["cs.RO"],"primary_cat":"cs.CV","authors_text":"Chunyu Li, Liangzheng Sun, Mengfan He, Xingyu Shao, Ziyang Meng","submitted_at":"2026-02-27T10:15:15Z","abstract_excerpt":"To address the scale mismatch caused by large altitude variations in UAV visual place recognition, we propose a monocular vision-only altitude-adaptive geo-localization framework. The method first estimates relative altitude from a single downward-looking image by transforming the input into the frequency domain and formulating altitude estimation as a regression-as-classification (RAC) problem. The estimated altitude is then used to crop the query image to a canonical scale, after which a classification-then-retrieval visual place recognition module performs coarse localization. To improve re"},"claims":{"count":4,"items":[{"kind":"strongest_claim","text":"With our visual place recognition module, altitude adaptation improves average R@1 and R@5 by 41.50 and 56.83 percentage points, respectively, compared with using the same retrieval pipeline without altitude normalization.","source":"verdict.strongest_claim","status":"machine_extracted","claim_id":"C1","attestation":"unclaimed"},{"kind":"weakest_assumption","text":"Relative altitude can be reliably estimated from a single downward-looking image by frequency-domain transformation formulated as a regression-as-classification problem, supplying an effective scale prior that benefits downstream visual place recognition under significant altitude variations.","source":"verdict.weakest_assumption","status":"machine_extracted","claim_id":"C2","attestation":"unclaimed"},{"kind":"one_line_summary","text":"A vision-only system estimates altitude from one downward image to normalize scale and improve UAV geo-localization accuracy under large height changes.","source":"verdict.one_line_summary","status":"machine_extracted","claim_id":"C3","attestation":"unclaimed"},{"kind":"headline","text":"Estimating relative altitude from one downward image normalizes scale and raises UAV retrieval recall by over 40 points.","source":"verdict.pith_extraction.headline","status":"machine_extracted","claim_id":"C4","attestation":"unclaimed"}],"snapshot_sha256":"e3b6a5737d06905542424ff2f657a2598e98895ccb1b3db733c5c35d0ca27745"},"source":{"id":"2602.23872","kind":"arxiv","version":3},"verdict":{"id":"5c10d2d0-88fe-465c-92cc-761e9a3a1ed4","model_set":{"reader":"grok-4.3"},"created_at":"2026-05-15T18:59:31.106454Z","strongest_claim":"With our visual place recognition module, altitude adaptation improves average R@1 and R@5 by 41.50 and 56.83 percentage points, respectively, compared with using the same retrieval pipeline without altitude normalization.","one_line_summary":"A vision-only system estimates altitude from one downward image to normalize scale and improve UAV geo-localization accuracy under large height changes.","pipeline_version":"pith-pipeline@v0.9.0","weakest_assumption":"Relative altitude can be reliably estimated from a single downward-looking image by frequency-domain transformation formulated as a regression-as-classification problem, supplying an effective scale prior that benefits downstream visual place recognition under significant altitude variations.","pith_extraction_headline":"Estimating relative altitude from one downward image normalizes scale and raises UAV retrieval recall by over 40 points."},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2602.23872/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":2,"snapshot_sha256":"3bdbced86dd79cdb299288e30ca8bf19779030c7aa70de8f5fa2dca25f6c7fbb"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"}