Oct 3, 2020 · We propose a method that produces realistic 3D augmented images from multiple viewpoints with different illumination conditions through 3D face modeling.
Experiments demonstrate that the proposed 3D data augmentation method significantly improves the performance and robustness of various face understanding ...
3D-Aided Data Augmentation for Robust Face Understanding ... Data augmentation has been highly effective in narrowing the data gap and reducing the cost for human ...
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Oct 21, 2019 · It consists of two alternate modules: adversarial sample generating for 3D face data augmentation and meta-learning-based deep network training.
Expression and pose variations are major challenges for reliable face recognition (FR) in 2D. In this paper, we aim to endow state of the art face ...
Dec 2, 2023 · In this paper, we propose a novel robust low-quality 3D face recognition method based on Facial Adversarial Sample Augmentation, namely FASA-3DFR.
Missing: Aided | Show results with:Aided
We introduce a set of image transformations that can be used as corruptions to evaluate the robustness of models as well as data augmentation mechanisms for ...
In our study, we propose a novel framework that combines GANs, SVM, and DenseNet architectures to enhance 3D human posture data augmentation for motion quality ...
A Dual-Agent Generative Adversarial Network (DA-GAN) model is proposed, which can improve the realism of a face simulator's output using unlabeled real ...
May 8, 2023 · 论文标题： 3D-Aided Data Augmentation for Robust Face Understanding（ 用于鲁棒人脸理解的3D辅助数据增强） 作者： Yifan Xing，Yuanjun Xiong，Wei Xia