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Found 3 papers, 1 papers with code
Optimizing Negative Prompts for Enhanced Aesthetics and Fidelity in Text-To-Image Generation
In text-to-image generation, using negative prompts, which describe undesirable image characteristics, can significantly boost image quality.
UAlberta at SemEval-2023 Task 1: Context Augmentation and Translation for Multilingual Visual Word Sense Disambiguation
We present a novel algorithm that leverages glosses retrieved from BabelNet, in combination with text and image encoders.
Semantically-Prompted Language Models Improve Visual Descriptions
With both ideas, we demonstrate that V-GLOSS improves visual descriptions and achieves strong results in the zero-shot setting on general and fine-grained image-classification datasets, including ImageNet, STL-10, FGVC Aircraft, and Flowers 102.
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