Free-hand sketches are highly illustrative, and have been widely used by humans to depict
objects or stories from ancient times to the present. The recent prevalence of touchscreen …

Learning meaningful representations of free-hand sketches remains a challenging task
given the signal sparsity and the high-level abstraction of sketches. Existing techniques …

Sketching or doodling is a popular creative activity that people engage in. However, most
existing work in automatic sketch understanding or generation has focused on sketches that …

We introduce SketchGNN, a convolutional graph neural network for semantic segmentation
and labeling of freehand vector sketches. We treat an input stroke-based sketch as a graph …

Sketch is a well-researched topic in the vision community by now. Sketch semantic
segmentation in particular, serves as a fundamental step towards finer-level sketch …

We consider the cross-modal alignment problem for free-hand sketch. Given a sequence of
stroke and a rasterized image, the objective is to enhance the performance of sketch …

We present the first one-shot personalized sketch segmentation method. We aim to segment
all sketches belonging to the same category provisioned with a single sketch with a given …

Sketch recognition relies on two types of information, namely, spatial contexts like the local
structures in images and temporal contexts like the orders of strokes. Existing methods …

We present a generative model for stroke-based drawing tasks which is able to model
complex free-form structures. While previous approaches rely on sequence-based models …

Sketch semantic segmentation is a well-explored and pivotal problem in computer vision
involving the assignment of predefined part labels to individual strokes. This paper presents …