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Whareformer egocentric video tracking paper

Whareformer: Learning to Track What is Where in Long Egocentric Videos

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Dima Damen Evangelos Kazakos

“Whareformer @eccv.bsky.social #ECCV2026 fantastic collab bw @compscibristol.bsky.social @naverlabseurope.bsky.social by Jacob Chalk w/ @sinhasaptarshi.bsky.social @skamalas.bsky.social & @dlarlus.bsky.social Paper, Code &models public: jacobchalk.github.io/…”

2 experts discussed this · 7 posts
Dima Damen: NEW Whareformer: Learning to Track What is Where in Long Egocentric Videos @eccvconf #ECCV2026 paper The first online learning approach to track dynamic objects in ego video reasoning on appearance…
Dima Damen: Whareformer (What&Where former) tackles the OSNOM task - Out of Sight objects remain explicitly in memory so you know where objects are at all times. In natural ego videos, tracking moving objects …
Dima Damen: We train: * embedding network g(.) to combine appearance &location diff * NT token to learn to initialise new tracks * transformer encoder to contrast assignments Memory is updated online based on …
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Primary source arxiv.org ↗ jacobchalk.github.io ↗