태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
Vehicle Color Recognition (VCR) involves developing a system to automatically identify and classify the color of vehicles from images or video footage. This task is essential for enhancing vehicle recognition systems, particularly in surveillance, law enforcement, and traffic management applications. The goal is to accurately categorize vehicles based on color, despite challenges such as varying lighting conditions, shadows, and low-resolution images.
출처에 같은 태스크 이름으로 연결된 데이터셋입니다. 동명 태스크가 포함될 수 있으므로, 비교할 때는 평가 결과의 조건도 확인하세요.
The UFPR-VCR dataset contains 10,039 images of 9,502 distinct vehicles across various categories, including cars, vans, buses, and trucks. The images capture a broad spectrum of real-world conditions, such as frontal and rear views, partial occlusions, diverse lighting situations, and nighttime scenes. The dataset was designed to address Vehicle Color Recognition (VCR) in more challenging scenarios than those explored in previous studies.
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.