Humans can easily perceive the direction of sound sources in a visual scene, termed sound
source localization. Recent studies on learning-based sound source localization have …

Abstract Leveraging Large Language Models' remarkable proficiency in text-based tasks,
recent works on Multi-modal LLMs (MLLMs) extend them to other modalities like vision and …

Audio-visual segmentation (AVS) aims to segment the sounding objects in video frames.
Although great progress has been witnessed we experimentally reveal that current methods …

Large-scale pre-trained image-text models demonstrate remarkable versatility across
diverse tasks, benefiting from their robust representational capabilities and effective …

Abstract Audio–Visual Segmentation (AVS) aims to extract the sounding objects from a
video. The current learning-based AVS methods are often supervised, which rely on specific …

The joint analysis of audio and video is a powerful tool that can be applied to various
contexts, including action, speech, and sound recognition, audio-visual video parsing …

The objective of the sound source localization task is to enable machines to detect the
location of sound-making objects within a visual scene. While the audio modality provides …

The goal of the multi-sound source localization task is to localize sound sources from the
mixture individually. While recent multi-sound source localization methods have shown …

Recent studies on learning-based sound source localization have mainly focused on the
localization performance perspective. However, prior work and existing benchmarks …

By observing a scene and listening to corresponding audio cues, humans can easily
recognize where the sound is. To achieve such cross-modal perception on machines …