Arbitrary　style　transfer　means　that　stylized　images　can　be　generated　from　a　set　of　arbitrary　input　image　pairs　of　content　images　and　style　images.　Recent　arbitrary　style　transfer　algorithms　lead　to　distortion　of　content　or　incompletion　of　style　transfer　because　network　need　to　make　a　balance　between　the　content　structure　and　style.　In　this　paper,　we　introduce　a　dual　attention　network　based　on　style　attention　and　channel　attention,　which　can　flexibly　transfer　local　styles,　pay　more　attention　to　content　structure,　keep　content　structure　intact　and　reduce　unnecessary　style　transfer.　Experimental　results　show　that　the　network　can　synthesize　high　quality　stylized　images　while　maintaining　real-time　performance.　©　2021　IEEE.