Jul 18, 2019 · In this paper, we propose an approach for multi-class sketch semantic segmentation by considering it as a sequence-to-sequence generation ...

We investigate the problem of stroke-level sketch segmentation, which is to automatically assign strokes of a given sketch with semantic labels.

This paper proposes an approach for multi-class sketch semantic segmentation by considering it as a sequence-to-sequence generation problem, and presents an ...

ABSTRACT We investigate the problem of stroke-level sketch segmentation, which is to automatically assign strokes of a given sketch with semantic labels.

SketchSegNet+: An End-to-End Learning of RNN for Multi-Class Sketch Semantic Segmentation ... Sketch-based Image Retrieval via Siamese Convolutional Neural ...

SketchSegNet+: An End-to-End Learning of RNN for Multi-Class Sketch Semantic Segmentation, IEEE Access 2019. Fast Sketch Segmentation and Labeling With Deep ...

This paper treats the problem of stroke-level sketch segmentation as a seqence-to-sequence generation problem, and a reccurent nueral networks (RNN)-based ...

Sketchsegnet: A rnn model for labeling sketch strokes. X Wu, Y ... SketchSegNet+: An end-to-end learning of RNN for multi-class sketch semantic segmentation.

SketchSegNet+: An End-to-end Learning of RNN for Multi-Class Sketch Semantic Segmentation. Article. Full-text available. Jul 2019. Yonggang Qi ...

Sketch semantic segmentation is a well-explored and pivotal problem in computer vision involving the assignment of pre-defined part labels to individual ...