基于注意力機制和ACT網(wǎng)絡(luò)的人臉圖像修復(fù)
打開文本圖片集
Face image inpainting based on attention mechanism and ACT network
TENGLin1，2，ZHANGQian12，XU Kaili2 （1.SchoolofData Scienceand InformationEngineering，Guizhou Minzu University，Guiyang 55oo25，China; 2.KeyLaboratoryofPatternRecognitionand InteligentSystemsofGuizhouProvince，Guiyang55O025，China）
Abstract：A faceimage inpainting method basedonconvolutional block atentionmodule（CBAM）andaggregated contextualtransformation（ACT）network isproposed tomakethecompletionofmissingsemanticfeaturesinfacialimages more realisticandtoenhancetherecoveryofdetailedinformation.Inthismethod，thetwobranchesofthebaselinemodelareretained. Inthesemanticandimagfilteringbranches，theCBAMlayersareaddedtocapturethecriticaldetailinformationforfilingthe mising areas intheimages.Thebaseline residual blocksarereplaced withACTresidual blocks，which can preserve therich detailsoutsidethemissingareasandcaptureabundantcontextualinformation.Thismadethesemanticinformationfilinginthis branchmoreaccurate，efectivelyremovedartifactsandenrichedimagedetails.Inthekernelpredictionbranch，thetwomodules areadded toenhancethereceptivefieldandcontextualreasoning perception when extracting image features，makingthedynamic predictionof filtering kernelsmore precise.Thismethod wasvalidatedontheCelebA-HQdataset，showing improvements in quantitative metrics such as PSNR （peak signal-to-noise ratio），SSIM （structural similarity index measure）and L1 . The qualitative repairresultsarealsoclearerandmorenatural.Thestudyconfirmsthattheproposed methodhavegoodeffectivenessforfacial image inpainting.
Keywords：image inpainting; CBAMatentionmechanism;ACTnetwork;encoder-decoder;facial image inpainting;mage filtering
0 引言
圖像修復(fù)是指重建圖像中缺失區(qū)域的任務(wù)。（剩余10343字）