Building upon Miller's framework of explanations derived from research in multiple

Neural Information Processing Systems http://nips.cc/

Vision transformer networks have shown superiority in many computer vision tasks.

The DViSal dataset is hosted on GitHub, and is supported and maintained by the authors.

Inthis paper,wepresent anend-to-end collaborative aggregation-and-distribution network (CoADNet) to capture both salient and repetitive visual patterns from multiple images. First, we integrate saliencypriors intothebackbone features tosuppress theredundant background information through an online intra-saliency guidance structure. After that, we design a two-stage aggregate-and-distribute architecture to explore group-wise semantic interactions and produce theco-saliencyfeatures.