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cs.CV2026

Micro-Expression-Aware Avatar Fingerprinting via Inter-Frame Feature Differencing

Masoumeh Chapariniya, Jean-Marc Odobez, Volker Dellwo +1

Avatar fingerprinting, i.e., verifying who drives a synthetic talking-head video rather than whether it is real, is a critical safeguard for authorized use of face-reenactment tech…

cs.CV2026

Foundation Model Embeddings Meet Blended Emotions: A Multimodal Fusion Approach for the BLEMORE Challenge

Masoumeh Chapariniya, Aref Farhadipour, Sarah Ebling +2

We present our system for the BLEMORE Challenge at FG 2026 on blended emotion recognition with relative salience prediction. Our approach combines six encoder families through late…

cs.CV2026

Adaptive Multimodal Person Recognition: A Robust Framework for Handling Missing Modalities

Aref Farhadipour, Teodora Vukovic, Volker Dellwo +2

Person identification systems often rely on audio, visual, or behavioral cues, but real-world conditions frequently present with missing or degraded modalities. To address this cha…

cs.CV2025

Investigating Identity Signals in Conversational Facial Dynamics via Disentangled Expression Features

Masoumeh Chapariniya, Pierre Vuillecard, Jean-Marc Odobez +2

This work investigates whether individuals can be identified solely through the pure dynamical components of their facial expressions, independent of static facial appearance. We l…

cs.CV2025

Beyond Appearance: Transformer-based Person Identification from Conversational Dynamics

Masoumeh Chapariniya, Teodora Vukovic, Sarah Ebling +1

This paper investigates the performance of transformer-based architectures for person identification in natural, face-to-face conversation scenario. We implement and evaluate a two…

cs.CV2025

Two-Stream Spatial-Temporal Transformer Framework for Person Identification via Natural Conversational Keypoints

Masoumeh Chapariniya, Hossein Ranjbar, Teodora Vukovic +2

In the age of AI-driven generative technologies, traditional biometric recognition systems face unprecedented challenges, particularly from sophisticated deepfake and face reenactm…