  Sight and hearing are two senses that play a vital role in human
communication and scene understanding. To mimic human perception ability,
audio-visual learning, aimed at developing computational approaches to learn
from both audio and visual modalities, has been a flourishing field in recent
years. A comprehensive survey that can systematically organize and analyze
studies of the audio-visual field is expected. Starting from the analysis of
audio-visual cognition foundations, we introduce several key findings that have
inspired our computational studies. Then, we systematically review the recent
audio-visual learning studies and divide them into three categories:
audio-visual boosting, cross-modal perception and audio-visual collaboration.
Through our analysis, we discover that, the consistency of audio-visual data
across semantic, spatial and temporal support the above studies. To revisit the
current development of the audio-visual learning field from a more macro view,
we further propose a new perspective on audio-visual scene understanding, then
discuss and analyze the feasible future direction of the audio-visual learning
area. Overall, this survey reviews and outlooks the current audio-visual
learning field from different aspects. We hope it can provide researchers with
a better understanding of this area. A website including constantly-updated
survey is released: \url{https://gewu-lab.github.io/audio-visual-learning/}.
