Deep self-supervised representation learning for free-hand sketch
In this paper, we tackle for the first time, the problem of self-supervised representation
learning for free-hand sketches. This importantly addresses a common problem faced by the …
learning for free-hand sketches. This importantly addresses a common problem faced by the …
Deep learning for free-hand sketch: A survey
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 …
objects or stories from ancient times to the present. The recent prevalence of touchscreen …
Sketch-bert: Learning sketch bidirectional encoder representation from transformers by self-supervised learning of sketch gestalt
Previous researches of sketches often considered sketches in pixel format and leveraged
CNN based models in the sketch understanding. Fundamentally, a sketch is stored as a …
CNN based models in the sketch understanding. Fundamentally, a sketch is stored as a …
Fs-coco: Towards understanding of freehand sketches of common objects in context
We advance sketch research to scenes with the first dataset of freehand scene sketches, FS-
COCO. With practical applications in mind, we collect sketches that convey scene content …
COCO. With practical applications in mind, we collect sketches that convey scene content …
Freehand sketch recognition using deep features
RK Sarvadevabhatla, RV Babu - arXiv preprint arXiv:1502.00254, 2015 - arxiv.org
Freehand sketches often contain sparse visual detail. In spite of the sparsity, they are easily
and consistently recognized by humans across cultures, languages and age groups …
and consistently recognized by humans across cultures, languages and age groups …
Sketch-a-net: A deep neural network that beats humans
We propose a deep learning approach to free-hand sketch recognition that achieves state-of-
the-art performance, significantly surpassing that of humans. Our superior performance is a …
the-art performance, significantly surpassing that of humans. Our superior performance is a …
Sketchformer: Transformer-based representation for sketched structure
Sketchformer is a novel transformer-based representation for encoding free-hand sketches
input in a vector form, ie as a sequence of strokes. Sketchformer effectively addresses …
input in a vector form, ie as a sequence of strokes. Sketchformer effectively addresses …
Learning structural representations via dynamic object landmarks discovery for sketch recognition and retrieval
State-of-the-art methods on sketch classification and retrieval are based on deep
convolutional neural network to learn representations. Although deep neural networks have …
convolutional neural network to learn representations. Although deep neural networks have …
Picture that sketch: Photorealistic image generation from abstract sketches
Given an abstract, deformed, ordinary sketch from untrained amateurs like you and me, this
paper turns it into a photorealistic image-just like those shown in Fig. 1 (a), all non-cherry …
paper turns it into a photorealistic image-just like those shown in Fig. 1 (a), all non-cherry …
Vectorization and rasterization: Self-supervised learning for sketch and handwriting
Self-supervised learning has gained prominence due to its efficacy at learning powerful
representations from unlabelled data that achieve excellent performance on many …
representations from unlabelled data that achieve excellent performance on many …