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The FaceX dataset is released under the Creative Conmmons Attribution 3.0 Unported License. Any commercial usage please contact iDVx lab in advance.
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A Dataset Containing Hand-Drawing Sketches

The dataset contains over 5 million labeled facial sketches categorized by genders (male, female), viewing angles (frontal, mid-profile left view), and emotions (neutral, happy, sad, angry, fearful, surprised, disgusted).

SVG format:

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NPZ format:

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FaceX Dataset is Drawn by a Group of Designers

In total, the designers drew 2,205 pairs of eyebrows, 2,016 pairs of eyes, 1,806 noses, and 2,058 mouths that satisfy aesthetic criteria. We combined these hand-drawn facial features into different faces and placed these facial features according to the divine proportion of the human head.

FaceX has the diversity to meet the requirements from different designers.

Two genders

Three artistic styles

Two viewing angles

Six basic emotions

Download the FaceX Dataset

We provide two data formats of FaceX.

SVG Format: 56.2MB

Scalable Vector Graphics. An XML-based vector image format for two-dimensional graphics with support for interactivity and animation.
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NPZ Format: 112.4MB

The stroke vector format used for training the model.
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Citation

Citation is given to the following publication:

  • Yang Shi, Nan Cao, Xiaojuan Ma, Siji Chen and Pei Liu. 2020. EmoG: Supporting the Sketching of Emotional Expressions for Storyboarding. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems. 393:1-393:12.
  • Nan Cao, Xin Yan, Yang Shi, Chaoran Chen. 2019. AI-Sketcher: A Deep Generative Model for Generating High Quality Sketches. In Proceedings of the AAAI Conference on Artificial Intelligence. 2564–2571.

@InProceedings{ shi2020emog, title = {EmoG: Supporting the Sketching of Emotional Expressions for Storyboarding}, author = {Shi, Yang and Cao, Nan and Ma, Xiaojuan and Chen, Siji and Liu, Pei}, booktitle = {Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems}, pages = {393:1--393:12}, year = {2020} }

@InProceedings{ cao2019aisketcher, title = {AI-Sketcher: A Deep Generative Model for Producing High Quality Sketches}, author = {Cao, Nan and Yan, Xin and Shi, Yang and Chen, Chaoran}, booktitle = {Proceedings of the AAAI Conference on Artificial Intelligence}, pages = {2564--2571}, year = {2019} }