Papers › Who's Waldo? Linking People Across Text and Images

Who's Waldo? Linking People Across Text and Images

16 Aug 2021ICCV 2021 10arXiv:2108.07253archive 2025-07-28

Claire Yuqing Cui, Apoorv Khandelwal, Yoav Artzi, Noah Snavely, Hadar Averbuch-Elor

We present a task and benchmark dataset for person-centric visual grounding, the problem of linking between people named in a caption and people pictured in an image. In contrast to prior work in visual grounding, which is predominantly object-based, our new task masks out the names of people in captions in order to encourage methods trained on such image-caption pairs to focus on contextual cues (such as rich interactions between multiple people), rather than learning associations between names and appearances. To facilitate this task, we introduce a new dataset, Who's Waldo, mined automatically from image-caption data on Wikimedia Commons. We propose a Transformer-based method that outperforms several strong baselines on this task, and are releasing our data to the research community to spur work on contextual models that consider both vision and language.

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clairecyq/whos-waldo officialmentioned on GitHubpytorch report

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Tasks

Person-centric Visual Grounding

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Introduced by this paper, per the archive.

Who’s Waldo

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
Person-centric Visual Grounding Who’s Waldo Who's Waldo Accuracy 63.5 #1 of 1 Archive leaderboard report

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