CAD modeling, despite being the industry-standard, remains restricted to usage by skilled
practitioners due to two key barriers. First, the user must be able to mentally parse a final …

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 …

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 …

Abstract Convolutional Neural Networks (CNNs) have always been the dominant method for
scene sketch semantic segmentation, but their performance seems to have plateaued due to …

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 …

With the recent surge in the use of touchscreen devices, free-hand sketching has emerged
as a promising modality for human-computer interaction. While previous research has …

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 study the underexplored but fundamental vision problem of machine understanding of
abstract freehand scene sketches. We introduce a sketch encoder that results in …

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 …