452 citations · 1k across the 29 of their papers we have counts for
3 papers · 1 filter
DiffiT: Diffusion Vision Transformers for Image Generation
Ali Hatamizadeh, Jiaming Song, Guilin Liu +2
Diffusion models with their powerful expressivity and high sample quality have achieved State-Of-The-Art (SOTA) performance in the generative domain. The pioneering Vision Transfor…
ViR: Towards Efficient Vision Retention Backbones
Ali Hatamizadeh, Michael Ranzinger, Shiyi Lan +3
Vision Transformers (ViTs) have attracted a lot of popularity in recent years, due to their exceptional capabilities in modeling long-range spatial dependencies and scalability for…
FasterViT: Fast Vision Transformers with Hierarchical Attention
Ali Hatamizadeh, Greg Heinrich, Hongxu Yin +4
We design a new family of hybrid CNN-ViT neural networks, named FasterViT, with a focus on high image throughput for computer vision (CV) applications. FasterViT combines the benef…