Breakfast Cereal Product Occlusion Image Dataset

The retail e-commerce industry faces significant challenges in accurately recognizing products that are partially occluded on shelves. Current solutions primarily focus on fully visible items, leading to a lack of robust models for occluded scenarios. The Breakfast Cereal Product Occlusion Image Dataset aims to bridge this gap by providing a diverse set of occluded images of popular brands like Kellogg's, Quaker, and Nestlé. This dataset features images collected under various conditions, using high-resolution cameras in retail environments that simulate real-world conditions. Quality control measures include multiple rounds of annotations, consistency checks, and expert reviews to ensure data accuracy. The dataset is organized in JPG format, with structured folders categorized by product types and occlusion levels.