The　fabric　defect　detection　algorithm　based　on　object　detection　has　become　a　research　hotspot.　The　method　based　on　the　Single　Shot　MultiBox　Detector　(SSD)　model　has　a　fast　detection　speed,　but　the　detection　accuracy　is　insufficient.　To　balance　the　detection　speed　and　accuracy　of　the　model　and　meet　the　actual　needs　of　the　industry,　an　improved　fabric　defect　detection　algorithm　based　on　SSD　is　proposed　in　this　study.　The　Fully　Convolutional　Squeeze-and-Excitation　(FCSE)　block　is　added　into　the　traditional　SSD　to　improve　the　detection　accuracy　of　the　model.　The　number　of　default　boxes　was　adjusted　to　accommodate　the　detection　of　long　strip　defects　on　fabric　surface.　Experimental　results　on　the　TILDA　and　Xuelang　dataset　confirm　that　our　detection　method　based　on　SSD　efficiently　detected　various　fabric　defects.　©　2021　American　Association　of　Textile　Chemists　and　Colorists.