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Found 3 papers, 3 papers with code
Scalable High-Resolution Pixel-Space Image Synthesis with Hourglass Diffusion Transformers
We present the Hourglass Diffusion Transformer (HDiT), an image generative model that exhibits linear scaling with pixel count, supporting training at high-resolution (e. g. $1024 \times 1024$) directly in pixel-space.
LAION-5B: An open large-scale dataset for training next generation image-text models
We show successful replication and fine-tuning of foundational models like CLIP, GLIDE and Stable Diffusion using the dataset, and discuss further experiments enabled with an openly available dataset of this scale.
VQGAN-CLIP: Open Domain Image Generation and Editing with Natural Language Guidance
Generating and editing images from open domain text prompts is a challenging task that heretofore has required expensive and specially trained models.
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