PoseKernelLifter: Metric Lifting of 3D Human Pose using Sound

Yang, Zhijie; Fan, Xiaoran; Isler, Volkan; Park, Hyun Soo

doi:10.1109/cvpr52688.2022.01283

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Increasing Importance of Joint Analysis of Audio and Video in Computer Vision: A Survey

Shahabaz,

Sarkar

2024

IEEE Access

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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, emotion recognition in affective computing, and self-supervised training of deep learning models. Solving these problems often involves tackling core audio-visual tasks, such as audio-visual source localization, audio-visual correspondence, and audio-visual source separation, which can be combined in various ways to achieve the desired results. This paper provides a review of the literature in this area, discussing the advancements, history, and datasets of audio-visual learning methods for various application domains. It also presents an overview of the reported performances on standard datasets and suggests promising directions for future research. INDEX TERMS computer vision, audio-video analysis, contrastive learning, multi-modal analysis

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