RFOP: Rethinking Fusion and Orthogonal Projection for Face-Voice Association

2025/12/02 by Hannan, Abdul, Malik, Furqan, Jabbar, Hina +2 · 1 citation
#Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences

paper · doi:10.48550/arxiv.2512.02860

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.

Citations

• Face-voice Association in Multilingual Environments (FAME) 2026 Challenge Evaluation Plan
• PAEFF: Precise Alignment and Enhanced Gated Feature Fusion for Face-Voice Association
• Single-branch Network for Multimodal Training
• Speaker Recognition in Realistic Scenario Using Multimodal Data
• Fusion and Orthogonal Projection for Improved Face-Voice Association
• Cross-modal Speaker Verification and Recognition: A Multilingual Perspective
• Deep Latent Space Learning for Cross-modal Mapping of Audio and Visual Signals
• Learnable PINs: Cross-Modal Embeddings for Person Identity
• Seeing Voices and Hearing Faces: Cross-modal biometric matching

Cited by

• Linking Faces and Voices Across Languages: Insights from the FAME 2026 Challenge

Related

• Exploring Robust Face-Voice Matching in Multilingual Environments
• Face-voice Association in Multilingual Environments (FAME) 2026 Challenge Evaluation Plan
• Face-voice Association in Multilingual Environments (FAME) Challenge 2024 Evaluation Plan
• Linking Faces and Voices Across Languages: Insights from the FAME 2026 Challenge
• Shared Multi-modal Embedding Space for Face-Voice Association