Papers › DAD-3DHeads: A Large-scale Dense, Accurate and Diverse Dataset for 3D Head Alignment...

DAD-3DHeads: A Large-scale Dense, Accurate and Diverse Dataset for 3D Head Alignment from a Single Image

7 Apr 2022CVPR 2022 1arXiv:2204.03688archive 2025-07-28

Tetiana Martyniuk, Orest Kupyn, Yana Kurlyak, Igor Krashenyi, Jiři Matas, Viktoriia Sharmanska

We present DAD-3DHeads, a dense and diverse large-scale dataset, and a robust model for 3D Dense Head Alignment in the wild. It contains annotations of over 3.5K landmarks that accurately represent 3D head shape compared to the ground-truth scans. The data-driven model, DAD-3DNet, trained on our dataset, learns shape, expression, and pose parameters, and performs 3D reconstruction of a FLAME mesh. The model also incorporates a landmark prediction branch to take advantage of rich supervision and co-training of multiple related tasks. Experimentally, DAD-3DNet outperforms or is comparable to the state-of-the-art models in (i) 3D Head Pose Estimation on AFLW2000-3D and BIWI, (ii) 3D Face Shape Reconstruction on NoW and Feng, and (iii) 3D Dense Head Alignment and 3D Landmarks Estimation on DAD-3DHeads dataset. Finally, the diversity of DAD-3DHeads in camera angles, facial expressions, and occlusions enables a benchmark to study in-the-wild generalization and robustness to distribution shifts. The dataset webpage is https://p.farm/research/dad-3dheads.

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PinataFarms/DAD-3DHeads officialmentioned on GitHubpytorchNOASSERTION report

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Tasks

3D ReconstructionDiversityHead Pose EstimationPose Estimation

Datasets

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DAD-3DHeads

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
Head Pose Estimation AFLW2000 DAD-3DNet MAE 3.66 #7 of 25 Archive leaderboard report
Head Pose Estimation BIWI DAD-3DNet MAE (trained with BIWI data) 3.98 #26 of 29 Archive leaderboard report

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