RFOP: Rethinking Fusion and Orthogonal Projection for Face-Voice Association
Abdul Hannan
Furqan Malik
Hina Jabbar
Syed Suleman Sadiq
Mubashir Noman
- CVBM

Main:1 Pages
1 Figures
Bibliography:1 Pages
2 Tables
Appendix:1 Pages
Abstract
Face-voice association in multilingual environment challenge 2026 aims to investigate the face-voice association task in multilingual scenario. The challenge introduces English-German face-voice pairs to be utilized in the evaluation phase. To this end, we revisit the fusion and orthogonal projection for face-voice association by effectively focusing on the relevant semantic information within the two modalities. Our method performs favorably on the English-German data split and ranked 3rd in the FAME 2026 challenge by achieving the EER of 33.1.
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