Search Results for author:
Found 3 papers, 2 papers with code
3D Face Reconstruction with the Geometric Guidance of Facial Part Segmentation
In this paper, we fully utilize the facial part segmentation geometry by introducing Part Re-projection Distance Loss (PRDL).
Safe Self-Refinement for Transformer-based Domain Adaptation
Unsupervised Domain Adaptation (UDA) aims to leverage a label-rich source domain to solve tasks on a related unlabeled target domain.
Shuffle Augmentation of Features from Unlabeled Data for Unsupervised Domain Adaptation
Unsupervised Domain Adaptation (UDA), a branch of transfer learning where labels for target samples are unavailable, has been widely researched and developed in recent years with the help of adversarially trained models.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
