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20202024
most citedDCFace: Synthetic Face Generation with Dual Condition Diffusion Model

4 citations · 12 across the 6 of their papers we have counts for

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5 papers · 1 filter

cs.CV20242 cited

KeyPoint Relative Position Encoding for Face Recognition

Minchul Kim, Yiyang Su, Feng Liu +2

In this paper, we address the challenge of making ViT models more robust to unseen affine transformations. Such robustness becomes useful in various recognition tasks such as face…

cs.CV20232 cited

FRCSyn Challenge at WACV 2024:Face Recognition Challenge in the Era of Synthetic Data

Pietro Melzi, Ruben Tolosana, Ruben Vera-Rodriguez +44

Despite the widespread adoption of face recognition technology around the world, and its remarkable performance on current benchmarks, there are still several challenges that must…

cs.CV20233 cited

Learning Clothing and Pose Invariant 3D Shape Representation for Long-Term Person Re-Identification

Feng Liu, Minchul Kim, ZiAng Gu +2

Long-Term Person Re-Identification (LT-ReID) has become increasingly crucial in computer vision and biometrics. In this work, we aim to extend LT-ReID beyond pedestrian recognition…

cs.CV20234 cited

DCFace: Synthetic Face Generation with Dual Condition Diffusion Model

Minchul Kim, Feng Liu, Anil Jain +1

Generating synthetic datasets for training face recognition models is challenging because dataset generation entails more than creating high fidelity images. It involves generating…

cs.CV2022

Controllable and Guided Face Synthesis for Unconstrained Face Recognition

Feng Liu, Minchul Kim, Anil Jain +1

Although significant advances have been made in face recognition (FR), FR in unconstrained environments remains challenging due to the domain gap between the semi-constrained train…