ChartReformer: Natural Language-Driven Chart Image Editing

arXiv:2403.00209v1 Announce Type: new
Abstract: Chart visualizations are essential for data interpretation and communication; however, most charts are only accessible in image format and lack the corresponding data tables and supplementary information, making it difficult to alter their appearance for different application scenarios. To eliminate the need for original underlying data and information to perform chart editing, we propose ChartReformer, a natural language-driven chart image editing solution that directly edits the charts from the input images with the given instruction …

abstract application arxiv charts communication cs.cv data editing format image information interpretation language making natural natural language tables type