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Found 3 papers, 1 papers with code
ChartReformer: Natural Language-Driven Chart Image Editing
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.
SpaDen : Sparse and Dense Keypoint Estimation for Real-World Chart Understanding
A combination of sparse and dense per-pixel objectives coupled with a uni-modal self-attention-based feature-fusion layer is applied to learn KP embeddings.
Context-Aware Chart Element Detection
As a prerequisite of chart data extraction, the accurate detection of chart basic elements is essential and mandatory.
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