6 papers
TECCI: Tricky Edits of Collected and Curated Images
Aishwarya Agrawal, Roy Hirsch, Yasumasa Onoe +2
Despite tremendous recent progress, current text-guided image editing methods still struggle with many aspects of editing involving instruction following, minimally editing the sou…
Unblocking Fine-Grained Evaluation of Detailed Captions: An Explaining AutoRater and Critic-and-Revise Pipeline
Brian Gordon, Yonatan Bitton, Andreea Marzoca +4
Large Vision-Language Models (VLMs) now generate highly detailed, paragraphlength image captions, yet evaluating their factual accuracy remains challenging. Current methods often m…
Revisiting Text-to-Image Evaluation with Gecko: On Metrics, Prompts, and Human Ratings
Olivia Wiles, Chuhan Zhang, Isabela Albuquerque +11
While text-to-image (T2I) generative models have become ubiquitous, they do not necessarily generate images that align with a given prompt. While previous work has evaluated T2I al…
ImageInWords: Unlocking Hyper-Detailed Image Descriptions
Roopal Garg, Andrea Burns, Burcu Karagol Ayan +7
Despite the longstanding adage "an image is worth a thousand words," generating accurate hyper-detailed image descriptions remains unsolved. Trained on short web-scraped image text…
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…
DOCCI: Descriptions of Connected and Contrasting Images
Yasumasa Onoe, Sunayana Rane, Zachary Berger +9
Vision-language datasets are vital for both text-to-image (T2I) and image-to-text (I2T) research. However, current datasets lack descriptions with fine-grained detail that would al…