CVPR2025
DefectFill: Realistic Defect Generation with Inpainting Diffusion Model for Visual Inspection
Jaewoo Song, Daemin Park, Kanghyun Baek, Sangyub Lee, Jooyoung Choi, Eunji Kim, Sungroh Yoon
Abstract
Reference Defect MVTec Images Real World Images Figure 1 . Given a few reference image-mask pairs of a defect (e.g. "hole" of a hazelnut), DefectFill learns the defect and realistically fill it onto defect-free objects in desired shapes (e.g. star, square, etc.), generating new defect images that integrate naturally with the objects. These generated images are then used for visual inspection tasks.