mlsanityData to 14 Oct 2026

PACE: Polar Axis-Conditioned Estimation for PairUAV Relative Localization

arXiv 2607.17268 ↗First posted 19 Jul 2026cs.CVcited by 0

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Abstract (arXiv)

PairUAV relative localization maps two UAV images to a polar navigation command. Although heading and range share the same pairwise pose context, treating them as homogeneous coordinates forces both outputs to use the same decoder evidence and optimization state. Controlled readout probes reveal a different structure: the two axes favor different decoder-depth combinations, their best checkpoints disagree on 80.8% of a validation trajectory, and range errors exhibit a distinct high-error tail. We introduce method, Polar Axis-Conditioned Estimation, which retains a shared Reloc3r-style pair representation while assigning axis-specific readout interfaces. Heading uses mid/late relational evidence, whereas range remains attached to a direct late metric path. On the official hidden test, the strongest released raw predictor scores 0.002460; the complementary PAAER predictor scores 0.002514 with a slightly lower angle error. Deterministic challenge packaging, reported separately from learned estimation, yields the final score of 0.001874. Code, checkpoints, predictions, and reconstruction tools are available at https://github.com/zerong7777-boop/PairUAV-PACE.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 11 of its 14 references that are in the map. First posted on arXiv 19 Jul 2026.

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References · 11

  1. 2017Multi-Task Learning Using Uncertainty to Weigh Losses for Scene Geometry and Semanticscited by 1,358
  2. 2020Gradient Surgery for Multi-Task Learningcited by 1,256
  3. 2021LoFTR: Detector-Free Local Feature Matching with Transformerscited by 984
  4. 2024Grounding Image Matching in 3D with MASt3Rcited by 983
  5. 2017GradNorm: Gradient Normalization for Adaptive Loss Balancing in Deep Multitask Networkscited by 834
  6. 2022TransGeo: Transformer Is All You Need for Cross-view Image Geo-localizationcited by 168
  7. 2020University-1652: A Multi-view Multi-source Benchmark for Drone-based Geo-localizationcited by 157
  8. 2024Reloc3r: Large-Scale Training of Relative Camera Pose Regression for Generalizable, Fast, and Accurate Visual Localizationcited by 82
  9. 2023Towards Natural Language-Guided Drones: GeoText-1652 Benchmark with Spatial Relation Matchingcited by 42
  10. 2022Multiple-environment Self-adaptive Network for Aerial-view Geo-localizationcited by 37
  11. 2026Last-Meter Precision Navigation for UAVs: A Diffusion-Refined Aerial Visual Servoing Approachcited by 3

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