DermSynth3D: Synthesis of in-the-wild Annotated Dermatology Images

arXiv:2305.12621v3 Announce Type: replace-cross
Abstract: In recent years, deep learning (DL) has shown great potential in the field of dermatological image analysis. However, existing datasets in this domain have significant limitations, including a small number of image samples, limited disease conditions, insufficient annotations, and non-standardized image acquisitions. To address these shortcomings, we propose a novel framework called DermSynth3D. DermSynth3D blends skin disease patterns onto 3D textured meshes of human subjects using a differentiable renderer and generates 2D images from various …

arxiv cs.cv cs.lg dermatology eess.iv images synthesis type