Book ChapterDOI
IIIT-CFW: A Benchmark Database of Cartoon Faces in the Wild
Ashutosh Mishra,Shyam Nandan Rai,Anand Mishra,C. V. Jawahar,C. V. Jawahar +4 more
- pp 35-47
TLDR
This database contains 8,928 annotated images of cartoon faces of 100 public figures and will be useful in conducting research on spectrum of problems associated with cartoon understanding.Abstract:
In this paper, we introduce the cartoon faces in the wild (IIIT-CFW) database and associated problems. This database contains 8,928 annotated images of cartoon faces of 100 public figures. It will be useful in conducting research on spectrum of problems associated with cartoon understanding. Note that to our knowledge, such realistic and large databases of cartoon faces are not available in the literature.read more
Citations
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Proceedings ArticleDOI
Learning from the Past: Meta-Continual Learning with Knowledge Embedding for Jointly Sketch, Cartoon, and Caricature Face Recognition
TL;DR: This paper proposes a novel framework termed as Meta-Continual Learning with Knowledge Embedding to address the task of jointly sketch, cartoon, and caricature face recognition, and presents a deep relational network to capture and memorize the relation among different samples.
Proceedings ArticleDOI
Deep Cross Modal Learning for Caricature Verification and Identification (CaVINet)
TL;DR: In this article, a cross modal architecture was proposed to handle extreme distortions of caricatures using a deep learning network that learns similar representations across the modalities, which achieved 85% rank-1 accuracy for caricatures and 95% accuracy for visual images.
Proceedings ArticleDOI
A Relation Network Embedded with Prior Features for Few-Shot Caricature Recognition
TL;DR: A novel relation network via meta learning is proposed to address the problem of few-shot caricature face recognition and combines learned deep and handcrafted features to form the hybrid-prior representation via joint meta learning.
Posted Content
Bringing Cartoons to Life: Towards Improved Cartoon Face Detection and Recognition Systems
TL;DR: This work employs various state-of-the-art deep learning frameworks for detecting and recognizing faces of cartoon characters along with proposing a novel approach to cartoon face recognition and demonstrates the effectiveness of the Multi-task Cascaded Convolutional Network (MTCNN) architecture.
Posted Content
Landmark Detection and 3D Face Reconstruction for Caricature using a Nonlinear Parametric Model
TL;DR: 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.
References
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