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Found 5 papers, 3 papers with code
Generative AI for Visualization: State of the Art and Future Directions
From a technical perspective, this paper looks back on previous visualization studies leveraging GenAI and discusses the challenges and opportunities for future research.
The Contemporary Art of Image Search: Iterative User Intent Expansion via Vision-Language Model
Moreover, the intent expansion framework enables users to perform flexible contextualized interactions with the search results to further specify or adjust their detailed search intents iteratively.
TimeTuner: Diagnosing Time Representations for Time-Series Forecasting with Counterfactual Explanations
Deep learning (DL) approaches are being increasingly used for time-series forecasting, with many efforts devoted to designing complex DL models.
Let the Chart Spark: Embedding Semantic Context into Chart with Text-to-Image Generative Model
Pictorial visualization seamlessly integrates data and semantic context into visual representation, conveying complex information in a manner that is both engaging and informative.
Everyone Can Be Picasso? A Computational Framework into the Myth of Human versus AI Painting
The recent advances of AI technology, particularly in AI-Generated Content (AIGC), have enabled everyone to easily generate beautiful paintings with simple text description.
