Video Pair

Video pair research focuses on understanding and leveraging the relationships between synchronized audio and video streams. Current efforts concentrate on improving the alignment and generation of audio-visual data using various deep learning architectures, including diffusion models, transformers, and convolutional neural networks, often employing contrastive learning or other techniques to enhance model performance. This work is significant for advancing applications such as low-light video enhancement, music visualization, and sound effect retrieval, ultimately improving the quality and realism of multimedia content and enabling new forms of interactive media.