FiTv2: Scalable and Improved Flexible Vision Transformer for Diffusion Model
The Flexible Vision Transformer (FiTv2) addresses limitations in existing diffusion models by treating images as variable-sized token sequences instead of fixed grids. FiT introduced this flexible approach, and FiTv2 enhances it with innovations like Query-Key vector normalization and AdaLN-LoRA. This results in a model capable of generating high-resolution images across unrestricted aspect ratios, achieving faster convergence and better scalability.