In recent years, computer science has made major advances in understanding drawing
behavior. Artificial intelligence, and more precisely deep learning, has displayed …

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 …

Sketch-based image retrieval (SBIR) utilizes sketches to search for images containing
similar objects or scenes. Due to the proliferation of touch-screen devices, sketching has …

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 …

The problem of sketch semantic segmentation is far from being solved. Despite existing
methods exhibiting near-saturating performances on simple sketches with high …

Hand-drawn sketch recognition is a fundamental problem in computer vision, widely used in
sketch-based image and video retrieval, editing, and reorganization. Previous methods often …

Sketch drawings play an important role in assisting humans in communication and creative
design since ancient period. This situation has motivated the development of artificial …

Online handwritten diagram recognition (OHDR) has attracted considerable attention for its
potential applications in many areas, but it is a challenging task due to the complex 2D …

We present a simple and efficient method based on deep learning to automatically
decompose sketched objects into semantically valid parts. We train a deep neural network to …

We investigate the problem of stroke-level sketch segmentation, which is to train machines
to assign strokes with semantic part labels given a input sketch. Solving the problem of …