Various federated transfer learning (FTL) methods have been proposed to address domain
shift and safeguard data privacy in the field of fault diagnosis. However, the effectiveness of …

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 …

The aim of audio-visual segmentation (AVS) is to precisely differentiate audible objects
within videos down to the pixel level. Traditional approaches often tackle this challenge by …

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 …

Given an audio-visual pair, audio-visual segmentation (AVS) aims to locate sounding
sources by predicting pixel-wise maps. Previous methods assume that each sound …

Abstract Audio-Visual Video Parsing (AVVP) task aims to detect and temporally locate
events within audio and visual modalities. Multiple events can overlap in the timeline …

This paper focuses on the Audio-Visual Question Answering (AVQA) task that aims to
answer questions derived from untrimmed audible videos. To generate accurate answers …

Humans possess a remarkable ability to integrate auditory and visual information enabling a
deeper understanding of the surrounding environment. This early fusion of audio and visual …

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 …

This paper introduces the task of Auditory Referring Multi-Object Tracking (AR-MOT), which
dynamically tracks specific objects in a video sequence based on audio expressions and …