QA4Camera

Smartphone has been one of the most popular digital devices in the past decades, with more than 300 million smartphones sold every quarter in the world wide. Most of the smartphone vendors, such as Apple, Huawei, Samsung, launch their new flagship smartphones every year. People use smartphone cameras to shoot selfie photos, film scenery or events, and record videos of family and friends. The specifications of smartphone camera and the quality of taken pictures are major criteria for consumer to select and buy smartphones. Many smartphone manufacturers also introduce and advertise their smartphones by introducing the strengths and advantages of their smartphone cameras. However, how to evaluate the quality of smartphone cameras and the taken pictures remains a problem for both smartphone manufacturers and confumers. Currently in the market, there are several teams and companies who evaluate the quality of smartphone cameras and announce the ranking and scores of the quality of smartphone cameras, and the scores of smartphone cameras are subjectively graded by several photographers and experts from different aspects, such as exposure, color, noise and texture. However, subjective assessment is not easy to reproduce, and it is not easy to deploy in practical image processing systems.In the last two decades, objective image quality assessment (IQA) has been widely researched, and a large amount of objective IQA algorithms have been designed to automatically and accurately estimate the quality of images. However, most of objective IQA methods are designed to assess the overall perceived quality of the image degraded by various simulated distortions, which rarely exist in pictures taken by the modern smartphone cameras. Thus these methods are not suitable for the task of smartphone camera quality assessment, while objective evaluation methods specifically designed for the purpose of smartphone camera quality assessment are relatively rare.The purpose of this Grand Challenge is to drive efforts of image quality assessment towards smartphone camera quality assessment. With this Grand challenge, it is expected to develop objective smartphone camera quality assessment models from four different aspects, including exposure, color, noise and texture, by using the datasets released by the organizers. The goal is to provide reference quality rankings or scores for smartphone cameras and to both smartphone manufacturers and consumers.Participants are asked to submit four computational models to cacluate the rankings of smartphone camera from four aspects: exposure, color, noise and texture.

近数十年来，智能手机始终是最普及的数字设备之一，全球每季度智能手机销量突破3亿台。包括苹果（Apple）、华为（Huawei）、三星（Samsung）在内的多数智能手机厂商，每年都会推出新一代旗舰机型。用户常借助智能手机摄像头拍摄自拍照片、记录风景与各类活动，或是录制亲友的日常影像。智能手机摄像头的硬件规格与成像画质，是消费者选购机型的核心考量标准之一。不少智能手机厂商也会通过宣传自身产品的摄像头优势，来推广旗下机型。然而，如何科学评估智能手机摄像头及其成像画质，始终是厂商与消费者共同面临的难题。当前市场上已有多家机构与团队开展智能手机摄像头画质评估业务，发布相关排名与评分；这类评分通常由多名摄影师与领域专家，从曝光、色彩、噪点、纹理等多个维度进行主观打分。但主观评估方法难以复现，也很难适配实际的图像处理系统落地应用。近二十年来，客观图像质量评估（Objective Image Quality Assessment, IQA）领域受到广泛研究，大量客观IQA算法被提出，用于自动、精准地评估图像质量。但绝大多数现有客观IQA方法，针对的是各类模拟失真导致画质下降的图像，而这类失真在现代智能手机的实拍图像中极少出现。因此这类方法并不适用于智能手机摄像头画质评估场景，而专门针对该场景设计的客观评估方法仍较为稀缺。本次大型挑战赛的宗旨，是推动图像质量评估领域向智能手机摄像头画质评估方向发展。依托主办方发布的数据集，本次挑战赛期望参赛者从曝光、色彩、噪点、纹理四个维度，研发针对性的智能手机摄像头画质客观评估模型。最终目标是为智能手机厂商与消费者提供兼具参考性的摄像头画质排名与评分。参赛者需提交四个计算模型，分别从曝光、色彩、噪点、纹理四个维度，对智能手机摄像头的画质进行排名计算。

搜集汇总

背景与挑战

背景概述

QA4Camera数据集旨在推动智能手机相机质量评估的研究，通过提供数据支持开发客观评估模型。该数据集聚焦于从曝光、颜色、噪声和纹理四个关键维度评估相机质量，以解决传统图像质量评估方法不适用于现代智能手机拍摄真实图片的问题。其目标是建立可重复、实用的评估体系，为智能手机制造商和消费者提供参考排名或分数。