🛰️ Remote Sensing¶

🎞️ ECCV2026 · 3 paper notes

Align and Segment: Unsupervised Learning for Building Segmentation From Misaligned Labels: Align and Segment (AnS) jointly learns building segmentation and geometric label correction, using self-supervised consistency and paired geometric augmentation to prevent memorized offsets, raising segmentation IoU from 0.39 for naive joint training to 0.78 on systematically misaligned Las Vegas data without clean aligned training labels.
Beyond 2D Matching: A Unified Single-Stage Framework for Geometry-Aware Cross-View Object Geo-Localization: GAGeo adapts the 3D foundation model π3 using CMA-Loc building correspondences and camera annotations, jointly decodes prompted objects and cameras in one forward pass, and uses satellite-anchored contrastive learning to reach 43.86 mAcc and 57.88 mIoU on the untrained ground-to-drone configuration.
Beyond Attention: Convolutional Global Context for Remote Sensing Change Detection: ChangeGCC conditions convolution kernels on scene-level descriptors, then combines intra-frame cross-scale aggregation with symmetric cross-temporal gating to detect remote sensing changes without a global pairwise attention matrix; its Base variant achieves 85.28% IoU on LEVIR-CD with 13.60M parameters.