11 citations · 21 across the 10 of their papers we have counts for
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cs.CV2024
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…
cs.CV2024
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…
cs.CV2024
DICE: Discrete Inversion Enabling Controllable Editing for Multinomial Diffusion and Masked Generative Models
Xiaoxiao He, Quan Dao, Ligong Han +14
Discrete diffusion models have achieved success in tasks like image generation and masked language modeling but face limitations in controlled content editing. We introduce DICE (D…