Skincare Product Occlusion Image Dataset

The skincare industry is rapidly evolving, with brands like Nivea, Cetaphil, Neutrogena, and La Roche-Posay facing challenges in accurately identifying products in various occluded conditions. Current solutions often fall short in handling occlusions and variations in product presentation. This dataset aims to address the technical issues surrounding product recognition under occlusion, which is crucial for improving visual search functionalities in e-commerce. The dataset comprises images collected from retail environments, featuring products in various occluded states. Data collection involved high-resolution photography under controlled lighting conditions to ensure clarity. Quality control was maintained through multiple rounds of annotation, consistency checks, and expert reviews to ensure a high level of accuracy. The images are stored in JPG format, organized by product categories and occlusion levels for easy access.