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cs.CV2024
AMO Sampler: Enhancing Text Rendering with Overshooting
Xixi Hu, Keyang Xu, Bo Liu +2
Achieving precise alignment between textual instructions and generated images in text-to-image generation is a significant challenge, particularly in rendering written text within…
cs.CV2024
Greedy Growing Enables High-Resolution Pixel-Based Diffusion Models
Cristina N. Vasconcelos, Abdullah Rashwan, Austin Waters +22
We address the long-standing problem of how to learn effective pixel-based image diffusion models at scale, introducing a remarkably simple greedy growing method for stable trainin…
cs.CV2024★ 1 cited
Inflation with Diffusion: Efficient Temporal Adaptation for Text-to-Video Super-Resolution
Xin Yuan, Jinoo Baek, Keyang Xu +2
We propose an efficient diffusion-based text-to-video super-resolution (SR) tuning approach that leverages the readily learned capacity of pixel level image diffusion model to capt…