Audio Visual
Audio-visual research focuses on understanding and leveraging the interplay between audio and visual information, primarily aiming to improve multimodal understanding and generation. Current research emphasizes developing sophisticated models, often employing transformer architectures and diffusion models, to achieve tasks like video-to-audio generation, audio-visual speech recognition, and emotion analysis from combined audio-visual data. This field is significant for its potential applications in various domains, including media production, accessibility technologies, and even mental health diagnostics, by enabling more robust and nuanced analysis of multimedia content.
Papers
Continuous-Time Audiovisual Fusion with Recurrence vs. Attention for In-The-Wild Affect Recognition
Vincent Karas, Mani Kumar Tellamekala, Adria Mallol-Ragolta, Michel Valstar, Björn W. Schuller
Continuous Emotion Recognition using Visual-audio-linguistic information: A Technical Report for ABAW3
Su Zhang, Ruyi An, Yi Ding, Cuntai Guan