Draw What Matters: Decoupling Stroke Capacity from Sketch Complexity in Photo-to-Vector Generation

A good sketch is an act of abstraction: it keeps what makes a subject recognizable and drops the rest. Most photo-to-vector methods, however, fix a stroke budget and render every stroke, so a single number sets both the $capacity$ of a sketch, how much it can express, and its $complexity$, how much it must show. Too few strokes lose recognizable parts, too many add clutter, and the right number changes from one image to the next. We present AdaSketch, which decouples the two: the budget only bounds capacity, and each stroke has to earn its visibility. AdaSketch draws one closed contour that secures the silhouette, plus a pool of detail strokes with learnable opacity. Which details survive is decided by coverage rather than by count: salient interior points must be covered (faithfulness), each by as few strokes as possible (conciseness), and a continuous parameter sets how much image-relevant detail to keep. A progressive contour-to-detail schedule settles where to draw before deciding which strokes to keep. Under the same budget, AdaSketch outperforms five existing methods on all five semantic, structural and perceptual metrics, adapts the rendered complexity to both content and the chosen abstraction level, and extends to target-specific sketching in multi-object scenes.