1 citations · 2 across the 8 of their papers we have counts for
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Self-Corrected Flow Distillation for Consistent One-Step and Few-Step Text-to-Image Generation
Quan Dao, Hao Phung, Trung Dao +2
Flow matching has emerged as a promising framework for training generative models, demonstrating impressive empirical performance while offering relative ease of training compared…
Supercharged One-step Text-to-Image Diffusion Models with Negative Prompts
Viet Nguyen, Anh Nguyen, Trung Dao +4
The escalating demand for real-time image synthesis has driven significant advancements in one-step diffusion models, which inherently offer expedited generation speeds compared to…
DiMSUM: Diffusion Mamba -- A Scalable and Unified Spatial-Frequency Method for Image Generation
Hao Phung, Quan Dao, Trung Dao +3
We introduce a novel state-space architecture for diffusion models, effectively harnessing spatial and frequency information to enhance the inductive bias towards local features in…
SwiftBrush v2: Make Your One-step Diffusion Model Better Than Its Teacher
Trung Dao, Thuan Hoang Nguyen, Thanh Le +4
In this paper, we aim to enhance the performance of SwiftBrush, a prominent one-step text-to-image diffusion model, to be competitive with its multi-step Stable Diffusion counterpa…