Publications (8)
Davidsonian Scene Graph: Improving Reliability in Fine-grained Evaluation for Text-to-Image Generation
Jaemin Cho, Yushi Hu, Roopal Garg +6
Evaluating text-to-image models is notoriously difficult. A strong recent approach for assessing text-image faithfulness is based on QG/A (question generation and answering), which…
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…
Imagen 3
Imagen-Team-Google, :, Jason Baldridge +257
We introduce Imagen 3, a latent diffusion model that generates high quality images from text prompts. We describe our quality and responsibility evaluations. Imagen 3 is preferred…
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…
Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities
Gheorghe Comanici, Eric Bieber, Mike Schaekermann +3431
In this report, we introduce the Gemini 2.X model family: Gemini 2.5 Pro and Gemini 2.5 Flash, as well as our earlier Gemini 2.0 Flash and Flash-Lite models. Gemini 2.5 Pro is our…
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…
Mismatch Quest: Visual and Textual Feedback for Image-Text Misalignment
Brian Gordon, Yonatan Bitton, Yonatan Shafir +5
While existing image-text alignment models reach high quality binary assessments, they fall short of pinpointing the exact source of misalignment. In this paper, we present a metho…
Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context
Gemini Team, Petko Georgiev, Ving Ian Lei +1132
In this report, we introduce the Gemini 1.5 family of models, representing the next generation of highly compute-efficient multimodal models capable of recalling and reasoning over…