Sketch Recognition
12 papers with code • 0 benchmarks • 3 datasets
Benchmarks
These leaderboards are used to track progress in Sketch Recognition
Quick, Draw! Dataset
ShoeV2
AtyPict
Latest papers with no code
SketchXAI: A First Look at Explainability for Human Sketches
Following this, we design a simple explainability-friendly sketch encoder that accommodates the intrinsic properties of strokes: shape, location, and order.
A hierarchical residual network with compact triplet-center loss for sketch recognition
Last but not least, the compact triplet-center loss is proposed specifically for the sketch recognition task.
Face Photo-Sketch Recognition Using Bidirectional Collaborative Synthesis Network
The problem of photo-sketch matching is challenging because 1) there is large modality gap between photo and sketch, and 2) the number of paired training samples is insufficient to train deep learning based networks.
On Training Sketch Recognizers for New Domains
We pose learning from small datasets as a key problem for the deep sketch recognition field, one which has been ignored in the bulk of the existing literature.
Identity-Aware CycleGAN for Face Photo-Sketch Synthesis and Recognition
Face photo-sketch synthesis and recognition has many applications in digital entertainment and law enforcement.
SketchAA: Abstract Representation for Abstract Sketches
The superiority of explicitly abstracting sketch representation is empirically validated on a number of sketch analysis tasks, including sketch recognition, fine-grained sketch-based image retrieval, and generative sketch healing.
A Study on various state of the art of the Art Face Recognition System using Deep Learning Techniques
Matching of derived sketches to photo images of face is also a difficult assignment as the considered sketches are produced upon the verbal explanation depicted by the eye witness of the crime scene and may have scarcity of sensitive elements that exist in the photograph as one can accurately depict due to the natural human error.
Sketch-Specific Data Augmentation for Freehand Sketch Recognition
Conventional methods for this task often rely on the availability of the temporal order of sketch strokes, additional cues acquired from different modalities and supervised augmentation of sketch datasets with real images, which also limit the applicability and feasibility of these methods in real scenarios.
SketchGAN: Joint Sketch Completion and Recognition With Generative Adversarial Network
Hand-drawn sketch recognition is a fundamental problem in computer vision, widely used in sketch-based image and video retrieval, editing, and reorganization.
Active Scene Learning
Several authors have attempted to address this issue by creating synthetic data, and by building tools that support efficient annotation.
