A Picture is Worth a Thousand Words: A Unified System for Diverse Captions and Rich Images Generation
This addresses the need for creative AI systems that can mimic human-like image-text interactions, though it appears incremental as it builds on existing multi-modal methods.
The paper tackles the problem of generating diverse captions for images and rich images from multiple captions, proposing a unified multi-modal Transformer framework that achieves real-time inference with non-autoregressive decoding.
A creative image-and-text generative AI system mimics humans' extraordinary abilities to provide users with diverse and comprehensive caption suggestions, as well as rich image creations. In this work, we demonstrate such an AI creation system to produce both diverse captions and rich images. When users imagine an image and associate it with multiple captions, our system paints a rich image to reflect all captions faithfully. Likewise, when users upload an image, our system depicts it with multiple diverse captions. We propose a unified multi-modal framework to achieve this goal. Specifically, our framework jointly models image-and-text representations with a Transformer network, which supports rich image creation by accepting multiple captions as input. We consider the relations among input captions to encourage diversity in training and adopt a non-autoregressive decoding strategy to enable real-time inference. Based on these, our system supports both diverse captions and rich images generations. Our code is available online.