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computer-vision-10

Caricature

3260 papers • 126 benchmarks • 313 datasets

Caricature is a pictorial representation or description that deliberately exaggerates a person’s distinctive features or peculiarities to create an easily identifiable visual likeness with a comic effect. This vivid art form contains the concepts of abstraction, simplification and exaggeration. Source: Alive Caricature from 2D to 3D

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Benchmarks

These leaderboards are used to track progress in caricature-10

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Dataset

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Libraries

i

Use these libraries to find caricature-10 models and implementations

Datasets

WebCaricature Dataset

WebCaricature Dataset

Subtasks

No subtasks available.

Most implemented papers

CariMe: Unpaired Caricature Generation With Multiple Exaggerations

Wenbin Li, Jing Huo, Yang Gao, Zheng Gu, C. Dong•Wed Sep 30 2020

A Multi-exaggeration Warper network is proposed to learn the distribution-level mapping from photos to facial exaggerations, which makes it possible to generate diverse and reasonable exaggerations from randomly sampled warp codes given one input photo.

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Content

Introduction Benchmarks Datasets Subtasks Libraries Papers

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Unpaired photo-to-caricature translation on faces in the wild

Nan Wang, Ziqiang Zheng, Chao Wang, Zhibin Yu, Haiyong Zheng, Bing Zheng•Tue Nov 28 2017

This work presents an approach for learning to translate faces in the wild from the source photo domain to the target caricature domain with different styles, which can also be used for other high-level image-to-image translation tasks.

34 0

Alive Caricature from 2D to 3D

Jianfei Cai, Yu-Kun Lai, Qianyi Wu, Juyong Zhang, Jianmin Zheng•Sun Mar 18 2018

An algorithm for creating expressive 3D caricatures from 2D caricature images with minimum user interaction is presented, to introduce an intrinsic deformation representation that has the capability of extrapolation, enabling us to create a deformation space from standard face datasets, which maintains face constraints and meanwhile is sufficiently large for producing exaggerated face models.

43 0

Learning to Zoom: a Saliency-Based Sampling Layer for Neural Networks

W. Matusik, A. Torralba, Simon Stent, Adrià Recasens, Petr Kellnhofer•Fri Sep 07 2018

A saliency-based distortion layer for convolutional neural networks that helps to improve the spatial sampling of input data for a given task and applies to improve existing networks for the tasks of human gaze estimation and fine-grained object classification.

143 0

Weakly-Supervised Caricature Face Parsing Through Domain Adaptation

Yi-Hsuan Tsai, Ming-Hsuan Yang, Deng Cai, Wei-Chih Hung, Wenqing Chu•Sun May 12 2019

This work formulate caricature face parsing as a domain adaptation problem, where real photos play the role of the source domain, adapting to the target caricatures, and first leverage a spatial transformer based network to enable shape domain shifts and a feed-forward style transfer network to capture texture-level domain gaps.

13 0

Dynamic Deep Multi-task Learning for Caricature-Visual Face Recognition

Zuheng Ming, J. Burie, M. Luqman•Sat Aug 31 2019

This paper proposes dynamic multi-task learning based on deep CNNs for cross-modal caricature-visual face recognition that dynamically updates the weights of tasks according to the importance of the tasks, which enables the training of the networks focus on the hard task instead of being stuck in the overtraining of the easy task.

2 0

3D-CariGAN: An End-to-End Solution to 3D Caricature Generation from Face Photos

Yu-Kun Lai, Yong-Jin Liu, Ran Yi, Zipeng Ye, Juyong Zhang, Minjing Yu•Sat Mar 14 2020

This paper proposes an end-to-end deep neural network model to generate high-quality 3D caricature with a simple face photo as input and introduces a simple- to-use interactive control with three horizontal and one vertical lines.

6 0

Landmark Detection and 3D Face Reconstruction for Caricature using a Nonlinear Parametric Model

Juyong Zhang, Yudong Guo, Hongrui Cai, Zhuang Peng•Sun Apr 19 2020

A neural network based method to regress the 3D face shape and orientation from the input 2D caricature image, and extensive experimental results demonstrate that the method works well for various caricatures.

36 0

AutoToon: Automatic Geometric Warping for Face Cartoon Generation

Julia Gong, Yannick Hold-Geoffroy, Jingwan Lu•Sat Feb 29 2020

This work proposes AutoToon, the first supervised deep learning method that yields high-quality warps for the warping component of caricatures, and can be paired with any stylization method to create diverse caricatures.

29 0

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Caricature | State-of-the-Art