Imagen: Text-to-Image Diffusion Models
We present Imagen, a text-to-image diffusion model with an unprecedented degree of photorealism and a deep level of language understanding. Imagen builds on the power of large transformer language models in understanding text and hinges on the strength of diffusion models in high-fidelity image generation.
Imagen Video
Imagen Video is another step forward in generative modelling capabilities, advancing text-to-video AI systems. Video generative models can be used to positively impact society, for example by amplifying and augmenting human creativity.
Imagen Editor & EditBench
To improve qualitative and quantitative evaluation, we introduce EditBench, a systematic benchmark for text-guided image inpainting. EditBench evaluates inpainting edits on natural and generated images exploring objects, attributes, and scenes.
Generative modeling has made tremendous progress with recent text-to-image systems like DALL-E 2 (Ramesh et al.,2022), Imagen (Saharia et al.,2022b), Parti (Yu et al.,2022), CogView (Ding et al.,2021) and Latent Diffusion (Rombach et al.,2022). Diffusion models (Sohl-Dickstein
Imagen: Text-to-Image Diffusion Models
Imagen: Text-to-Image Diffusion Models