Unconstrained Face Sketch Synthesis via Perception-Adaptive Network and A New Benchmark

  title={Unconstrained Face Sketch Synthesis via Perception-Adaptive Network and A New Benchmark},
  author={Lin Nie and Lingbo Liu and Zhengtao Wu and Wenxiong Kang},
1 Citations



A Sketch-Transformer Network for Face Photo-Sketch Synthesis

A Sketch-Transformer network for face photo-sketch synthesis is proposed, which consists of three closely-related modules, including a multi-scale feature and position encoder for patch-level feature and positions embedding, a self-attention module for capturing long-range spatial dependency, and amulti-scale spatially-adaptive de-normalization decoder for image reconstruction.

Semi-Supervised Learning for Face Sketch Synthesis in the Wild

A semi-supervised deep learning architecture is proposed which extends face sketch synthesis to handle face photos in the wild by exploiting additional facePhotos in training by performing patch matching in feature space between the input photo and photos in a small reference set of photo-sketch pairs.

Cascaded Face Sketch Synthesis Under Various Illuminations

It is argued that this framework paves a novel way for the implementation of computer-aided optical systems that are of essential importance in both face sketch synthesis and optical imaging.

Face Sketch Synthesis with Style Transfer Using Pyramid Column Feature

A novel framework based on deep neural networks for face sketch synthesis from a photo that outperforms other state-of-the-arts methods, and can also generalize well to different test images.

Neural Probabilistic Graphical Model for Face Sketch Synthesis

Experimental results demonstrate that the proposed NPGM-based face sketch synthesis approach can more effectively capture specific features and recover common structures compared with the state-of-the-art methods.

Iterative local re-ranking with attribute guided synthesis for face sketch recognition

Markov Random Neural Fields for Face Sketch Synthesis

A novel face sketch synthesis based on the Markov random neural fields including two structures, which can preserve the common structure and capture the characteristic features of the test photo, and achieves better results in terms of both quantitative and qualitative experimental evaluations.

Face Photo-Sketch Synthesis and Recognition

A novel face photo-sketch synthesis and recognition method using a multiscale Markov Random Fields (MRF) model that allows effective matching between the two in face sketch recognition.

Deep Graphical Feature Learning for Face Sketch Synthesis

This work presents a novel face sketch synthesis method combining generative exemplar-based method and discriminatively trained deep convolutional neural networks (dCNNs) via a deep graphical feature learning framework, which outperforms state-of-the-art methods in terms of both synthesis quality and recognition ability.