Author

Andrew Zisserman

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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 vision intelligence for the physical world.

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