Audio Visual Scene

Audio-visual scene understanding aims to analyze and interpret scenes by integrating information from both audio and visual data streams, enabling computers to perceive environments more comprehensively than with a single modality. Current research focuses on developing robust models, often employing transformer architectures and graph convolutional networks, to effectively fuse audio and visual features for tasks like scene classification, segmentation, and question answering. This field is crucial for advancing applications such as content verification, robot navigation, and assistive technologies by providing machines with a richer understanding of their surroundings.