AI RESEARCH
Honey, I Shrunk the Arc de Triomphe!
arXiv CS.CV
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ArXi:2606.02379v1 Announce Type: new Metric scale monocular geometry estimation has seen significant progress through large-scale data aggregation, yet current foundation models suffer from a persistent ''scale-collapse'' phenomenon: distant landmarks and vast landscapes are metrically underestimated. We hypothesize that this performance gap stems from a