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Author

Andrew Zisserman

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Preprint Sep 2026

SignMatch: Matching Dictionary Signs to Continuous Sign Language Video

A prototype-structured sign embedding space is learned from continuous video annotated with signs, where each learnable prototype corresponds to a sign class, enabling the matching between dictionary exemplars and continuous sign instances.

Ryan Wong, Youngjoon Jang, Liliane Momeni et al. · 0 citations
Preprint Sep 2026

TAPVid-MV: A Benchmark for Tracking Any Point in 3D Across Multiple Views

This work introduces TAPVid-MV (Tracking Any Point in Video across Multiple Views), the first benchmark for multi-view 3D point tracking, and identifies geometry recovery as a major bottleneck for accurate 3D point tracking.

Skanda Koppula, Frano Rajic, Abdullah Faiz Ur Rahman et al. · 1 citation
Preprint Jul 2026

Video Generation Models are General-Purpose Vision Learners

GenCeption is introduced, which leverages a pre-trained video generative diffusion backbone to define a feed-forward perception model, capable of performing various vision tasks steered by text instructions, and suggests that video generation is not merely a synthesis tool, but a foundational path toward generalist vis...

Letian Wang, Chuhan Zhang, Rishabh Kabra et al. · 6 citations
Preprint Jul 2026

Self-Supervised Learning of Structured Dynamics from Videos

The Structured Dynamics Model (SDM) is proposed, which explicitly separates the dominant source of temporal change from residual dynamics through future-feature prediction, rather than representing video change with a single entangled latent or with unstructured, spatially dense transition tokens.

Lukas Knobel, Andrew Zisserman, Yuki M. Asano · 0 citations

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