DAD-3DHeads: A Large-scale Dense, Accurate and Diverse Dataset for 3D Head Alignment from a Single Image
Paper
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2204.03688
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Published
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1
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Please use your institutional email for requesting the dataset access.
The "Researcher" has requested permission to use the DAD-3DHeads dataset (the "Dataset") created at Piñata Farms Inc. In exchange for such permission, Researcher hereby agrees to the following terms and conditions:
- Researcher shall use the Dataset for non-commercial research and educational purposes only.
- Researcher accepts full responsibility for them using the Dataset and shall defend and indemnify Piñata Farms Inc., including their employees, Trustees, officers and agents, against any and all claims arising from Researcher's use of the Dataset, including but not limited to Researcher's use of any copies of copyrighted images that they may create from the Dataset.
- The Dataset may not be passed to a third party, beyond the immediate research group of the Researcher.
- Piñata Farms Inc. reserves the right to terminate Researcher's access to the Dataset at any time.
- Researcher understands and is acknowledged that these images are provided 'as is', without any express or implied warranties of fitness for a particular purpose.
- All submitted papers (or any publicly available text) that uses the compound or partial images of the database must cite the following paper:
Tetiana Martyniuk*, Orest Kupyn*, Yana Kurlyak, Igor Krashenyi, Jiri Matas, Viktoriia Sharmanska: "DAD-3DHeads: A Large-scale Dense, Accurate and Diverse Dataset for 3D Head Alignment from a Single Image", CVPR 2022.
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DAD-3DHeads dataset
DAD-3DHeads dataset was introduced in the CVPR 2022 paper
DAD-3DHeads: A Large-scale Dense, Accurate and Diverse Dataset for 3D Head Alignment from a Single Image
Tetiana Martyniuk, Orest Kupyn, Yana Kurlyak, Igor Krashenyi, Jiři Matas, Viktoriia Sharmanska
Please use your institutional email for requesting the dataset access.
Useful links
The dataset structure is the following:
--train.tar
----images
------*.png
----annotations
------*.json
----train.json
--val.tar
----images
----annotations
----val.json
--test.tar
----images
----annotations
----test.json
Annotations *.json file structure:
--vertices
--model_view_matrix
--projection_matrix
Metadata train.json file structure:
--item_id
--annotation_path
--img_path
--bbox #[x, y, w, h] format
----0
----1
----2
----3
--attributes
----quality #[hq, lq]
----gender #[female, male, undefined]
----expression #[true, false]
----age #[child, young, middle_aged, senior]
----occlusions #[true, false]
----pose #[front, sided, atypical]
----standard light #[true, false]
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