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cs.CV2024
Layered Diffusion Model for One-Shot High Resolution Text-to-Image Synthesis
Emaad Khwaja, Abdullah Rashwan, Ting Chen +3
We present a one-shot text-to-image diffusion model that can generate high-resolution images from natural language descriptions. Our model employs a layered U-Net architecture that…
cs.CV2024
Subject-driven Text-to-Image Generation via Preference-based Reinforcement Learning
Yanting Miao, William Loh, Suraj Kothawade +3
Text-to-image generative models have recently attracted considerable interest, enabling the synthesis of high-quality images from textual prompts. However, these models often lack…