Apr 12, 2021 · Cross-modal biometric matching (CMBM) aims to determine the corresponding voice from a face, or identify the corresponding face from a voice ...

[11] train a two-branch neural network and achieve satisfactory matching results for CMBM. Wen et al. [12] attempt to learn a shared representation for the.

Apr 18, 2024 · Detach and Enhance: Learning Disentangled Cross-modal Latent Representation for Efficient Face-Voice Association and Matching ... To read the full ...

Disentangled Representation Learning for Cross-Modal Biometric Matching, 2021, TMM, ❎. FOP, Fusion and Orthogonal Projection for Improved Face-Voice ...

Disentangled Representation Learning for Cross-modal Biometric Matching. H Ning, X Zheng*, X Lu, Y Yuan. IEEE Transactions on Multimedia 24, 1763-1774, 2022.

Disentangled representation learning for cross-modal biometric matching. TMM, 2021. 3. [34] Yuval Nirkin, Yosi Keller, and Tal Hassner. Fsgan: Subject.

Mar 18, 2023 · Yuan, “Disentangled representation learning for cross-modal biometric matching,” IEEE Transactions on. Multimedia, vol. 24, pp. 1763-1774 ...

Apr 15, 2024 · Disentangled representation learning for cross-modal biometric matching. IEEE Transactions on Multimedia,. 24:1763–1774, 2022. 1, 2. 7. Page 8 ...

Abstract. One of the challenges in cross-age face recognition and verification is to effectively model the facial aging process. Despite the rapid advances in ...

How to Efficiently Achieve Cross-Modal Biometric Matching? Data：12-07-2021 ... disentangled representation learning for CMBM. The results were ...