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Akademický článek
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Low-light image enhancement (LLIE) is essential for numerous computer vision tasks, including object detection, tracking, segmentation, and scene understanding. Despite substantial research on improving low-quality images captured in underexposed con
Externí odkaz:
http://arxiv.org/abs/2410.09831
Autor:
Luo, Zhe, Fu, Weina, Liu, Shuai, Anwar, Saeed, Saqib, Muhammad, Bakshi, Sambit, Muhammad, Khan
Action detection and understanding provide the foundation for the generation and interaction of multimedia content. However, existing methods mainly focus on constructing complex relational inference networks, overlooking the judgment of detection ef
Externí odkaz:
http://arxiv.org/abs/2410.05771
Autor:
Islam, Md Tanvir, Rahim, Nasir, Anwar, Saeed, Saqib, Muhammad, Bakshi, Sambit, Muhammad, Khan
Publikováno v:
ACM Multimedia 2024
Reducing the atmospheric haze and enhancing image clarity is crucial for computer vision applications. The lack of real-life hazy ground truth images necessitates synthetic datasets, which often lack diverse haze types, impeding effective haze type c
Externí odkaz:
http://arxiv.org/abs/2409.17432
The no-reference image quality assessment is a challenging domain that addresses estimating image quality without the original reference. We introduce an improved mechanism to extract local and non-local information from images via different transfor
Externí odkaz:
http://arxiv.org/abs/2409.07115
Autor:
Qian, Chenghao, Rezaei, Mahdi, Anwar, Saeed, Li, Wenjing, Hussain, Tanveer, Azarmi, Mohsen, Wang, Wei
Adverse conditions like snow, rain, nighttime, and fog, pose challenges for autonomous driving perception systems. Existing methods have limited effectiveness in improving essential computer vision tasks, such as semantic segmentation, and often focu
Externí odkaz:
http://arxiv.org/abs/2409.02045
Large Language Models (LLMs) have demonstrated remarkable capabilities, revolutionizing the integration of AI in daily life applications. However, they are prone to hallucinations, generating claims that contradict established facts, deviating from p
Externí odkaz:
http://arxiv.org/abs/2406.09155
Advances in deepfake research have led to the creation of almost perfect manipulations undetectable by human eyes and some deepfakes detection tools. Recently, several techniques have been proposed to differentiate deepfakes from realistic images and
Externí odkaz:
http://arxiv.org/abs/2406.08625
In recent years, street view imagery has grown to become one of the most important sources of geospatial data collection and urban analytics, which facilitates generating meaningful insights and assisting in decision-making. Synthesizing a street-vie
Externí odkaz:
http://arxiv.org/abs/2405.08961
Human decision-making often relies on visual information from multiple perspectives or views. In contrast, machine learning-based object recognition utilizes information from a single image of the object. However, the information conveyed by a single
Externí odkaz:
http://arxiv.org/abs/2404.15224