Sketch Recognition

8 papers with code • 0 benchmarks • 2 datasets

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Most implemented papers

Sketch-a-Net that Beats Humans

dasayan05/sketchanet-quickdraw 30 Jan 2015

We propose a multi-scale multi-channel deep neural network framework that, for the first time, yields sketch recognition performance surpassing that of humans.

Enabling My Robot To Play Pictionary : Recurrent Neural Networks For Sketch Recognition

val-iisc/sketch-obj-rec 11 Aug 2016

In our work, we propose a recurrent neural network architecture for sketch object recognition which exploits the long-term sequential and structural regularities in stroke data in a scalable manner.

SketchMate: Deep Hashing for Million-Scale Human Sketch Retrieval

tosmaster/imagevision CVPR 2018

Key to our network design is the embedding of unique characteristics of human sketch, where (i) a two-branch CNN-RNN architecture is adapted to explore the temporal ordering of strokes, and (ii) a novel hashing loss is specifically designed to accommodate both the temporal and abstract traits of sketches.

Distribution-Aware Binarization of Neural Networks for Sketch Recognition

erilyth/DistributionAwareBinarizedNetworks-WACV18 9 Apr 2018

We present a theoretical analysis of the technique to show the effective representational power of the resulting layers, and explore the forms of data they model best.

Multi-Graph Transformer for Free-Hand Sketch Recognition

PengBoXiangShang/multigraph_transformer 24 Dec 2019

In this work, we propose a new representation of sketches as multiple sparsely connected graphs.

Sketch-BERT: Learning Sketch Bidirectional Encoder Representation from Transformers by Self-supervised Learning of Sketch Gestalt

avalonstrel/SketchBERT CVPR 2020

Unfortunately, the representation learned by SketchRNN is primarily for the generation tasks, rather than the other tasks of recognition and retrieval of sketches.

Edge Augmentation for Large-Scale Sketch Recognition without Sketches

nikosefth/im2rbte 26 Feb 2022

To bridge the domain gap we present a novel augmentation technique that is tailored to the task of learning sketch recognition from a training set of natural images.

Abstracting Sketches through Simple Primitives

explainableml/sketch-primitives 27 Jul 2022

Toward equipping machines with such capabilities, we propose the Primitive-based Sketch Abstraction task where the goal is to represent sketches using a fixed set of drawing primitives under the influence of a budget.