HQ-Edit: A High-Quality Dataset for Instruction-based Image Editing

arXiv:2404.09990v1 Announce Type: new
Abstract: This study introduces HQ-Edit, a high-quality instruction-based image editing dataset with around 200,000 edits. Unlike prior approaches relying on attribute guidance or human feedback on building datasets, we devise a scalable data collection pipeline leveraging advanced foundation models, namely GPT-4V and DALL-E 3. To ensure its high quality, diverse examples are first collected online, expanded, and then used to create high-quality diptychs featuring input and output images with detailed text prompts, followed by precise alignment …

arxiv cs.ai cs.cv dataset edit editing image quality type