Transcription of IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE …
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IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE …
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, MARCH 20201 Deep High-Resolution Representation Learningfor Visual RecognitionJingdong Wang, Ke Sun, Tianheng Cheng, Borui Jiang, Chaorui Deng, Yang Zhao, Dong Liu, Yadong Mu,Mingkui Tan, Xinggang Wang, Wenyu Liu, and Bin XiaoAbstract High-resolution representations are essential for position-sensitive vision problems, such as human pose estimation,semantic segmentation, and object detection. Existing state-of-the-art frameworks first encode the input image as a low-resolutionrepresentation through a subnetwork that is formed by connecting high-to-low resolution convolutionsin series( , ResNet,VGGNet), and then recover the high-resolution representation from the encoded low-resolution representation.
ing. Our multi-scale (resolution) fusion module resembles the two pooling modules. The differences include: (1) Our fusion outputs four-resolution representations other than only one, and (2) our fusion modules are repeated several times which is inspired by deep fusion [129], [143], [155], [178], [184]. Our approach. Our network connects high ...
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