Imagen
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About
Imagen is an advanced text-to-image diffusion model developed by Google Research's Brain Team, achieving unprecedented photorealism and deep language comprehension. It utilizes large transformer language models and diffusion techniques to generate high-fidelity images based on textual descriptions. By leveraging large pretrained language encoders, Imagen outperforms other models in both sample quality and image-text alignment, setting a new benchmark with an FID score of 7.27 on the COCO dataset without being trained on it. The new DrawBench benchmark further distinguishes Imagen's capabilities compared to models like DALL-E 2. Despite its strengths, Imagen faces ethical challenges, including potential biases in image generation and social implications due to its training data composition. To address these issues, the team has opted not to release the model publicly without further safeguards.
Platform
Task
Features
• generates photorealistic images from text descriptions
• addresses ethical concerns related to biases and data usage
• demonstrates significant improvement in image fidelity and quality over previous models
• introduces drawbench, a benchmark for evaluating text-to-image models
• employs large frozen t5-xxl encoder for text encoding
• utilizes advanced text-conditional diffusion models for image upsampling
• achieves state-of-the-art performance in image-text alignment
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