Foveated Diffusion: Efficient Spatially Adaptive Image and Video Generation
Diffusion and flow matching models have unlocked unprecedented capabilities for creative content creation, such as interactive image and streaming video generation. The growing demand for higher resolutions, frame rates, and context lengths, however, makes efficient generation increasingly challenging, as computational complexity grows quadratically with the number of generated tokens. Our work seeks to optimize the efficiency of the generation process in settings where the user's gaze location is known or can be estimated, for example, by using eye tracking. In these settings, we leverage the eccentricity-dependent acuity of human vision: while a user perceives very high-resolution visua...
| Authors | Brian Chao, Lior Yariv, Howard Xiao et al. |
|---|---|
| Primary category | cs.CV |
| Published | 24 March 2026 |
| Last updated at source | 24 March 2026 |
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