WEAK QUERY CALIBRATION FOR MULTI-VIEW UNIQUE COUNTING UNDER UNRELIABLE OVERLAP PROXIES

We introduce DAWSON, a weak-query calibration framework for multi-view unique counting with a small budget of aggregate shared-person answers. It treats each answer as sparse count-level supervision: per-view counts describe observations, while a queried pair supplies a shared-person cardinality without requiring cross-view identities. People visible in several cameras create duplicate mass, and appearance proxies weaken under occlusion, viewpoint changes, crop loss, and detector noise. Thus, the pair with the largest estimated overlap need not be the query that most improves the final union estimate. DAWSON combines per-view counts and pairwise overlap proxies into a fused unique-count estimate. Its expected union-error reduction (EER) rule evaluates candidate answers through an observable response surrogate and selects the query with the largest expected decrease in a calibration residual. The residual couples count consistency with uncertainty in unrevealed overlaps, so the weak-label budget follows the counting state. Each answer updates the fused estimate and ranking of remaining candidates. Selection uses observable counts, proxy similarities, and revealed responses, while keeping cross-view identities and the ground-truth unique count outside acquisition. Experiments on synthetic scenes and the static-camera WILDTRACK image-proxy bridge use annotation-simulated responses. With matched inputs, estimators, thresholds, and two-query budgets, EER yields lower paired MAE than Largest-overlap in all twelve degraded settings across four frozen encoders, with every paired 95% confidence interval below zero. The gap reaches −14.68 MAE for DINOv3 at Strong degradation. For YOLO26m, relative MAE reductions are 12.8%, 11.1%, and 13.2% at Mild, Medium, and Strong, and persist with noisy answers. Reliable-proxy controls retain Largest-overlap as a strong baseline, with same-input Max providing a zero-query reference for assessing weak-query calibration. These results establish residual-driven query selection as a proxy-regime-dependent mechanism for correcting overlap error under constrained budgets.