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Anh Totti Nguyen

Associate Professor of Computer Science, Auburn University

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  • Current Page Parent Research
  • Lab
  • Press
  • Work with me
  • Teaching
    • Courses
    • K-6 AI club
  • About
  • CV

change-detection-teaser

May 2025 0

At an optimal confidence threshold, CYWS [25] (top row) sometimes still produces false positives—□ in (a) & (c)—and fails to detect changes (a). Dashed - - - boxes show groundtruth changes. First, we encourage detectors to be more aware of changes via a novel contrastive loss. Second, our Hungarian-based post-processing reduces false positives (a), improves change-detection accuracy (b), and estimates correspondences (c–d), i.e., paired changes such as (□, □) and (□, □). Our work (bottom row) is the first to estimate change correspondences compared to prior works [25, 26, 40] (top row).

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  • Previous Improving zero-shot object-level change detection by incorporating visual correspondence
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