Recent text-to-image generation methods provide a simple yet exciting conversion capability between text and image domains. While these methods have incrementally improved the generated image fidelity and text relevancy, several pivotal gaps remain unanswered, limiting applicability and quality. We propose a novel text-to-image method that addresses these gaps by (i) enabling a simple control mechanism complementary to text in the form of a scene, (ii) introducing elements t… See more.
Recent text-to-image generation methods provide a simple yet exciting.
Conversion capability between text and image domains. While these methods have.
Incrementally improved the generated image fidelity and text relevancy, several.
Pivotal gaps remain unanswered, limiting applicability and quality. We propose.
A novel text-to-image method that addresses these gaps by (i) enabling a simple.
Control mechanism complementary to text in the form of a scene, (ii)
introducing elements that substantially improve the tokenization process by.
employing domain-specific knowledge over key image regions (faces and salient.
Comments are closed.