Jeans Occlusion Image Dataset

The retail e-commerce industry faces significant challenges in accurately recognizing clothing items due to occlusions that occur in various contexts, such as partially covered items in images. Existing solutions often struggle with robustness against such occlusions, leading to reduced accuracy in automated recognition systems. This dataset aims to address the specific technical challenges of occluded denim images, providing a diverse set of instances where jeans are obstructed by various elements like upper garments or seating positions. The data is collected using high-resolution cameras in controlled lighting environments, ensuring clarity and detail. Quality control measures include multiple rounds of annotation, consistency checks among annotators, and expert review to maintain high standards. The dataset is organized in a JPG format with clear labeling for each image's occlusion characteristics.