April 5, 2024, 4:46 a.m. | Jaeha Kim, Junghun Oh, Kyoung Mu Lee

cs.CV updates on arXiv.org arxiv.org

arXiv:2404.01692v2 Announce Type: replace
Abstract: In real-world scenarios, image recognition tasks, such as semantic segmentation and object detection, often pose greater challenges due to the lack of information available within low-resolution (LR) content. Image super-resolution (SR) is one of the promising solutions for addressing the challenges. However, due to the ill-posed property of SR, it is challenging for typical SR methods to restore task-relevant high-frequency contents, which may dilute the advantage of utilizing the SR method. Therefore, in this paper, …

arxiv beyond cs.cv image image recognition loss recognition resolution type

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