With the rapid increase in waste generation worldwide, efficient waste management has become a pressing environmental and economic challenge. Traditional waste sorting methods rely heavily on human labor, which is time-consuming, inconsistent, and costly. Computer vision-based automated waste sorting systems that use segmentation techniques can help classify and localize different types of waste effectively. This competition aims to develop models that can distinguish various waste categories with high precision, making waste management more efficient and scalable. By implementing such systems on conveyor belts in recycling facilities, we can enhance sorting accuracy and promote more effective recycling practices.