  Video salient object detection (VSOD), as a fundamental computer vision
problem, has been extensively discussed in the last decade. However, all
existing works focus on addressing the VSOD problem in 2D scenarios. With the
rapid development of VR devices, panoramic videos have been a promising
alternative to 2D videos to provide immersive feelings of the real world. In
this paper, we aim to tackle the video salient object detection problem for
panoramic videos, with their corresponding ambisonic audios. A multimodal
fusion module equipped with two pseudo-siamese audio-visual context fusion
(ACF) blocks is proposed to effectively conduct audio-visual interaction. The
ACF block equipped with spherical positional encoding enables the fusion in the
3D context to capture the spatial correspondence between pixels and sound
sources from the equirectangular frames and ambisonic audios. Experimental
results verify the effectiveness of our proposed components and demonstrate
that our method achieves state-of-the-art performance on the ASOD60K dataset.
